ALBERT

Description: 〈p〉Publication date: Available online 10 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Yaonan Shan, Kun She, Shouming Zhong, Jun Cheng, Wenyong Wang, Can Zhao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the passivity of Markovian jump discrete-time systems (MJDTSs) with channel fading via event-triggered state feedback control. First, the concerned MJDTSs contain infinitely distributed delays and switching rules with partially known transition probability (TP) information. Next, the fading channel, as an unreliable channel, is introduced into MJDTSs to better reflect the engineering practice in networked environment. Due to the present of channel fading, a series of random variables satisfying some certain probability density functions (PDFs) will be obstacles in the process of proof. Then, an event-triggered controller is designed for MJDTSs with channel fading and incomplete transition probability (ITP) for the first time. Thanks to this event-triggered mechanism, the state feedback control could greatly reduce energy consumption during transmission. Subsequently, under the above controller, we obtain some novel sufficient criteria in the form of linear matrix inequalities (LMIs) to ensure the passivity of closed-loop system. Finally, some simulation results are provided to demonstrate the feasibility and effectiveness of the proposed theoretical method.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 10 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Ahmed Bendib, Aissa Chouder, Kamel Kara, Abdelhammid Kherbachi, Said Barkat, Walid Issa〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In a microgrid (MG) topology, the secondary control is introduced to compensate for the voltage amplitude and frequency deviations, mainly caused by the inherent characteristics of the droop control strategy. This paper proposes an accurate approach to derive small signal models of the frequency and amplitude voltage at the point of common coupling (PCC) of a single-phase MG by analyzing the dynamics of the second-order generalized integrator-based frequency-locked loop (SOGI-FLL). The frequency estimate model is then introduced in the frequency restoration control loop, while the derived model of the amplitude estimate is introduced for the voltage restoration loop. Based on the obtained models, the MG stability analysis and proposed controllers’ parameters tuning are carried out. Also, this study includes the modeling and design of the synchronization control loop that enables a seamless transition from island mode to grid-connected mode operation. Simulation and practical experiments of a hierarchical control scheme, including traditional droop control and the proposed secondary control for two single-phase parallel inverters, are implemented to confirm the effectiveness and the robustness of the proposal under different operating conditions. The obtained results validate the proposed modeling approach to provide the expected transient response and disturbance rejection in the MG.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 4 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xi Wang, Shukai Li, Tao Tang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With the objective to promote the efficiency of heavy haul transportation, this paper investigates the efficiently intermittent cruise control problem for heavy haul trains. Based on the concept of periodically intermittent control, the closed-loop form of the error dynamic state-space model for heavy haul trains is given considering uncertain parameters, which is different from existing heavy haul train control methods in that the control forces are only provided in part of the running period. To facilitate the controller design, a set of linear matrix inequalities (LMIs) are presented as the sufficient conditions for the existence of the periodically intermittent controller, which guarantees both the speed tracking error and the relative coupler displacements are exponentially stable at the equilibrium state. Simulation results indicate that the proposed control scheme can significantly improve the control efficiency without sacrificing too much on speed tracking performance.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 4 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xin Hu, Chi Huang, Jianquan Lu, Jinde Cao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the stabilization problem of Boolean control networks with stochastic impulses, where stochastic impulses model is described as a series of possible regulatory models with corresponding probabilities. The stochastic impulses model makes the research more realistic. The global stabilization problem is trying to drive all states to reach the predefined target with probability 1. A necessary and sufficient condition is presented to judge whether a given system is globally stabilizable. Meanwhile, an algorithm is proposed to stabilize the given system by designing a state feedback controller and different impulses strategies. As an extension, these results are applied to analyze the global stabilization to a fixed state of probability Boolean control networks with stochastic impulses. Finally, two examples are given to demonstrate the effectiveness of the obtained results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Quanxin Zhu, S. Vimal Kumar, R. Raja, Fathalla Rihan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper addresses the issue of reliable feedback control of an uncertain aircraft flight control systems with disturbances via non-fragile sampled-data control approach. In particular, the parameter uncertainties are assumed to be randomly occurring which is described by the Bernoulli distributed sequences. By constructing a suitable Lyapunov-Krasovskii functional together with Wirtinger-based inequality, a new set of sufficient conditions in terms of linear matrix inequalities is obtained to ensure the asymptotic stability and extended dissipativity of the aircraft flight control systems not only when all actuators are operational, but also in case of some actuator failures. Finally, simulation results are conducted to validate the effectiveness of the proposed control design technique.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Cheng Tan, Zhongchang Liu, Wing Shing Wong〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the formation control of interconnected second-order systems. Each agent is assumed to be capable of measuring its own absolute velocity and the relative positions with respect to its neighboring agents, whereas the target formation is described by absolute positions of all agents in a global coordinate. For such formation control problems, no distributed control policy was reported in existing literature. This paper focuses on the string connection structure of the agents and proposes a distributed control policy that takes the form of purely state feedback without incorporating any feed-forward component. The closed-loop system equation is characterized by an oscillation matrix whose entries are the feedback controller gains. Formation control is accomplished by formulating the agents’ target positions as feedback controller gains. Moreover, it is shown that for agent models described by double integrators, each of the agents located at the two endpoints of the string structure should know its own absolute position. For a class of agent models where each agent’s acceleration depends on its own position, the control laws do not need to use the absolute position. For both system models, the target formations that are asymptotically reachable by the proposed control laws are specified explicitly. Numerical simulations have been conducted to illustrate the effectiveness of the theoretical results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 31 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Zhengjiang Zhang, Junghui Chen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The design, tuning, and implementation of controllers are crucial for the solutions to control problems. Generalized minimum variance control (GMVC) has attractive properties and it is widely used for controller performance enhancement. The measured signals of process output variables, which are used as feedback signals, are generally subject to measurement noise. However, the GMVC theory assumes the feedback signals are the process outputs, which rarely consider the unavoidable measurement noise. By additionally considering the measurement noise, the control performance of GMVC with the measurement noise is analyzed in this paper. The dynamic data reconciliation (DDR) method, which uses the information of both the process model and the measurement data to reconcile the measured signals, is introduced. It is combined with GMVC to reduce the effect of the measurement noise on the results of GMVC. The effectiveness of GMVC combined with DDR is illustrated in two case studies, where the proposed method is compared with the original GMVC and the GMVC with the conventional digital filter. The results in both SISO and MIMO control systems show that the proposed GMVC combined with DDR can reduce the effect of the measurement noise and achieve better control performance.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 31 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): P. Baziana, G. Fragkouli, E. Sykas〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper we study a multi-channel network, each station of which is equipped with a network interface that has a receiver buffer of multiple packets. In this way, each station is able to receive multiple packets per time instant. We adopt a synchronous access protocol which is affected by the collisions over the multiple channels and the destination conflicts. The proposed protocol performance crucially depends on the size of the receiver buffer since it determines the packet rejection probability at destination. An analytical probabilistic model based on a Markovian process is adopted for the performance measures derivation by means of closed mathematical formulas. The proposed protocol is compared to relative ones that either totally ignore the receiver collisions or assume a receiver buffer of a single packet capacity. The numerical results show that the increase of the receiver buffer size improves the performance decisively, resulting in higher throughput and lower delay and rejection probability. Also, it is shown that the appropriate receiver buffer size per station in order for the rejections at destination to be effectively eliminated is not unlimited but is limited to three packets for 0.1% accepted maximum level of rejection probability.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 17 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Chengyang Luo, Jianyong Yao, Jason Gu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents an extended state observer-based output feedback adaptive controller with a continuous LuGre friction compensation for a hydraulic servo control system. A continuous approximation of the LuGre friction model is employed, which preserves the main physical characteristics of the original model without increasing the complexity of the system stability analysis. By this way, continuous friction compensation is used to eliminate the majority of nonlinear dynamics in hydraulic servo system. Besides, with the development of a new parameter adaption law, the problems of parametric uncertainties are overcome so that more accurate friction compensation is realized. For another, the developed adaption law is driven by tracking errors and observation errors simultaneously. Thus, the burden of extended state observer to solve the remaining uncertainties is alleviated greatly and high gain feedback is avoided, which means better tracking performance and robustness are achieved. The designed controller handles not only matched uncertainties but also unmatched dynamics with requiring little system information, more importantly, it is based on output feedback method, in other words, the synthesized controller only relies on input signal and position output signal of the system, which greatly reduces the effects caused by signal pollution, measurement noise and other unexpected dynamics. Lyapunov-based analysis has proved this strategy presents a prescribed tracking transient performance and final tracking accuracy while obtaining asymptotic tracking performance in the presence of parametric uncertainties only. Finally, comparative experiments are conducted on a hydraulic servo platform to verify the high tracking performance of the proposed control strategy.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 9 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Engin H. Copur, Ahmet C. Arican, Sinan Ozcan, Metin U. Salamci〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉State Dependent Riccati Equation (SDRE) methods have the considerable advantages over other nonlinear control methods. However, stability issues can be arisen in SDRE based control system due to the lack of the global asymptotic stability property. Therefore, the previous studies have usually shown that local asymptotic stability can be ensured by estimating a Region of Attraction (ROA) around the equilibrium point. These estimated regions for stability may become narrow or the condition to keep the states in this region may be very conservative. To resolve these issues, this paper proposes a novel SDRE method employing an update algorithm to re-estimate the ROA when the states tend to move out of the stable region. The tendency is checked using a condition which is developed based on a new theorem. The theorem proves that it is possible to redesign the previous ROA with respect to the current states lying close to its boundary for ensuring the “non-local” stability along the trajectory without the need of solving SDRE at each time instant, unlike the standard SDRE approach. Therefore, the new theorem is now able to enhance the stability of the SDRE based closed-loop control system. The feasibility of the proposed SDRE control method is tested in both simulations and experiments. A validated 3-DOF laboratory helicopter is used for experiments and the control objective for the helicopter is to realise a preplanned movement in both elevation and travel axes. The results reveal that the proposed SDRE approach enables the controlled plant to track the desired trajectory as satisfactorily as the standard SDRE approach, while only solving SDRE when needed. The proposed SDRE method reduces the computational load for practical implementation of the control algorithm whilst ensuring the stability over the operational region.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 1 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Yi Dong, Shengyuan Xu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the rendezvous problem for a class of linear systems with uncertain parameters and external disturbances under the state-dependent dynamic network, which is also called rendezvous network here. By combining potential function technique, distributed internal model design and adaptive control technique, a distributed adaptive state feedback control law is proposed to solve the rendezvous problem by completing the tasks of maintaining the connectivity of the rendezvous network, achieving asymptotic tracking, rejecting unknown external disturbances as well as handling uncertain parameters in the system dynamics, the leader system and the exosystem simultaneously.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 31 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): R. Kavikumar, R. Sakthivel, O.M. Kwon, B. Kaviarasan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is concerned with the issue of finite-time boundedness of discrete-time uncertain interval type-2 fuzzy systems with time-varying delay and external disturbances via an observer-based reliable control strategy. According to the system output variable, a full-state observer that shares the same membership functions of the plant is constructed to estimate the unknown system states. In addition, a reliable controller subject to observer states and actuator faults is designed to formulate the closed-loop feedback control system, which does not share the same membership functions of the plant. Then, by constructing an appropriate Lyapunov–Krasovskii functional and using the finite-time stability theory, a new set of delay-dependent sufficient conditions guaranteeing the finite-time boundedness of the addressed system is established in the framework of linear matrix inequalities. Furthermore, the explicit expressions of gain matrices of the state observer and the reliable controller are given in terms of the established sufficient conditions. Finally, simulation results are presented to demonstrate the effectiveness of the obtained theoretical results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 17 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Kaixian Ba, Bin Yu, Qixin Zhu, Zhengjie Gao, Guoliang Ma, Zhengguo Jin, Xiangdong Kong〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the hydraulic drive unit(HDU) driving the joint motion of the legged robot is the research object. Through the experiment on HDU, it is observed that the control accuracy of the traditional position-based impedance control is not high enough. The further analysis researches the serial-parallel composition on dynamic compliances from both position control inner and impedance outer loop. Then, the two reasons affecting control accuracy are found out. Therefore, aimed at the first reason, a compliance-eliminated controller with multiple serial branches is designed. Aimed at the second reason, a feedforward compensation controller is designed. Finally, the dynamic compliance composition is rearranged. The results of experiments conducted indicate that the proposed method significantly improves the control accuracy compared to that of traditional position-based impedance control.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 9 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Zhihuan Chen, Xiaohui Yuan, Xiaotao Wu, Yanbin Yuan, Xiaohui Lei〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the frequency change problem of hydraulic turbine regulating system based on terminal sliding mode control method. By introducing a novel terminal sliding mode surface, a global fast terminal sliding mode controller is designed for the closed loop. This controller eliminates the slow convergence problem which arises in the terminal sliding mode control when the error signal is not near the equilibrium. Meanwhile, following consideration of the error caused by the actuator dead zone, an adaptive RBF estimator based on sliding mode surface is proposed. Through the dead zone error estimation for feed-forward compensation, the composite terminal sliding mode controller has been verified to possess an excellent performance without sacrificing disturbance rejection robustness and stability. Simulations have been carried out to validate the superiority of our proposed methods in comparison with other two other kinds of sliding mode control methods and the commonly used PID and FOPID controller. It is shown that the simulation results are in good agreement with the theoretical analysis.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 7 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Youmei Zhou, Jianwei Xia, Hao Shen, Jianping Zhou, Zhen Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The paper addresses the issue of extended dissipative learning for a class of delayed recurrent neural networks. Both time-varying delay and time-invariant delay are taken into account. By choosing appropriate Lyapunov–Krasovkii functionals and utilizing some inequalities, several weight learning rules are developed for ensuring the network to be asymptotically stable and extended dissipative. The existence conditions for these learning strategies consist of a few linear matrix inequalities, which are able to be verified readily by Matlab software. Two numerical examples are employed to show the effectiveness and low conservatism of the proposed learning rules.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 6 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Ticao Jiao, Ju H. Park, Cunshan Zhang, Yanlei Zhao, Kefeng Xin〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper deals with the stability problem of a class of stochastic switching singular systems with jumps, where all the continuous subsystems can be unstable. By introducing multiple time-varying discretized Lyapunov functions and designing novel switching signals via mode-dependent dwell times, sufficient conditions ensuring mean square and almost sure stabilities of the considered systems are obtained. On the basis of these findings, some existing results in the literature are further generalized. We finally provide a numerical example to verify the applicability of the proposed theoretical results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 5 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xinhe Wang, Zhen Wang, Jianwei Xia〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, a delayed fractional eco-epidemiological model with incommensurate orders is proposed, and a control strategy of this model is discussed. Firstly, for the system with no controller, the stability and Hopf bifurcation with respect to time delay are investigated. Secondly, under the influence of the controller, the stability and Hopf bifurcation of the system is discussed, and it is indicated that the stability of the system can be changed by increasing the feedback control delay. In particular, a separate study is carried out on the bifurcation with respect to the extended feedback delay, and the bifurcation point is calculated. At last, to support the theoretical results, some numerical simulations are depicted.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 16 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Junyuan Yang, Chairat Modnak, Jin Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Cholera is an infectious disease caused by the bacterium vibrio cholerae, which can lead to widespread epidemics in the deterioration of public health systems or the associated infrastructure. Vaccination and water sanitation are two well-known methods for the prevention and intervention of cholera epidemics. In this paper, we propose an age-structured cholera model that incorporates both the environment-to-human and human-to-human transmission pathways and that includes host vaccination and water sanitation as disease control measures. We rigorously investigate the threshold dynamics of this model using the basic reproduction number derived from our analysis. Meanwhile, we perform an optimal control study to explore cost-effective intervention strategies for cholera. Our numerical simulation results show that the outcome of the optimal control is shaped by the complex interactions among the age structure of the hosts, the costs of the control measures, the transmission modes of the disease, and the different approaches of cholera intervention.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 16 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xing Fang, Fei Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A novel coupling and disturbance characterization based control (CDC-BC) scheme is investigated for manned submersibles with strong couplings and disturbances. Firstly, the coupling characterization index (CCI) and disturbance characterization index (DCI) are defined to indicate whether the couplings and disturbances harm or benefit the manned submersible system. Then, the coupling and disturbance characterization based control (CDC-BC) method is developed to eliminate the detrimental couplings and disturbances, as well as to retain the beneficial ones. Moreover, it is also proved that the tracking errors of the closed-loop system will converge to zero asymptotically. Finally, some simulation results demonstrate the effectiveness of the proposed control scheme.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 7 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): S.H. Lee, M.J. Park, O.M. Kwon, R. Sakthivel〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this work, a sampled-data control problem for neural-network-based systems with an optimal guaranteed cost is investigated. By constructing suitable time-dependent functionals and utilizing an improved free-matrix-based integral inequality, a sampled-data stability criterion for neural-network-based systems is derived. Based on a first result, a sampled-data controller design method for neural-network-based systems that meets the maximum sampling period and minimum guaranteed cost performance is proposed. The superiority and validity of the results will be verified by comparing with the existing results in a numerical example.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 30 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Yazan M. Alsmadi, Alaa M. Abdelhamed, Abo Eleyoun Ellissy, Amged S. El-Wakeel, Almoataz Y. Abdelaziz, Vadim Utkin, Ali Arshad Uppal〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes an optimization scheme for optimal configuration and energy management of the micro-grid (MG), using the cuckoo search optimization algorithm (CSOA). The selected MG supplies a load profile located between 30.119 latitude and 31.605 longitude. The energy produced by the MG generation sources, according to meteorological data of the proposed location, is calculated using MATLAB. The objective/fitness function is modeled and designed for minimizing the total investment cost (TIC) including capital, investment, operation and maintenance costs. A novel weighted goal attainment function (WGAF) has been proposed to reduce CO〈sub〉2〈/sub〉 emissions and their associated costs. Moreover, WGAF also applies higher taxes on the amount of emissions that exceed governmental approved limits. To investigate the effects of WGAF on the TIC ($/year), annual cost of energy ($/kWh), and CO〈sub〉2〈/sub〉 emissions, various weighted coefficients are analyzed. The simulation results have shown that the designed optimization scheme can robustly and efficiently produce the optimal MG configuration that is both eco-friendly and generates economic benefits.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 28 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Ruimei Zhang, Deqiang Zeng, Ju H. Park, Shouming Zhong, Yajuan Liu, Xia Zhou〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, two new estimation approaches namely delay-dependent-matrix-based (DDMB) reciprocally convex inequality approach and DDMB estimation approach, are introduced for stability analysis of time-varying delay systems. Different from existing estimation techniques with constant matrices, the estimation approaches are with delay-dependent matrices, which can employ more free matrices and utilize more information of both time delay and its derivative. Based on the estimation approaches, less conservative stability criteria with lower computational complexity are derived in the form of linear matrix inequalities (LMIs). Finally, two numerical examples are given to illustrate the advantages of the proposed methods.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Ngo Phong Nguyen, Wonhee Kim, Jun Moon〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we consider the super-twisting observer-based sliding mode control algorithm with fuzzy variable gains (STOSMC) for the fully-actuated hexarotor. Our hexarotor has full actuation due to six titled propellers that allows to control position and orientation (attitude) simultaneously, and resolves the singularity problem of the rotational matrix by using the quaternion modeling framework. We show that the proposed STOSMC for the hexarotor guarantees finite-time convergence of the estimation error and asymptotic stability of the hexarotor. In simulations, we demonstrate the nonsingularity and fully-actuated control performance of the hexarotor by considering extreme position and attitude control scenarios. Moreover, the simulation results show that the hexarotor achieves the fast and precise tracking performance to the desired position and the desired attitude and the chattering phenomenon is reduced compared with the fixed-gains observer-based super-twisting sliding mode control due to the fuzzy mechanism.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): R. Samidurai, R. Sriraman〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper deals with the problem of non-fragile sampled-data stabilization analysis for a class of linear systems with probabilistic time-varying delays via new double integral inequality approach. Based on the auxiliary function-based integral inequality (AFBII) and with the help of some mathematical approaches, a new double integral inequality (NDII) is developed. Then, to demonstrate the merits of the proposed inequality, an appropriate Lyapunov-Krasovskii functional (LKF) is constructed with some augmented delay-dependent terms. By employing integral inequalities, an enhanced stability criterion for the concerned system model is derived in terms of linear matrix inequalities (LMIs). Finally, three benchmark illustrative examples are given to validate the effectiveness and advantages of the proposed results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Jiao-Jun Zhang, Hong-Sen Yan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In practice, many controlled plants are equipped with MIMO non-affine nonlinear systems. The existing methods for tracking control of time-varying nonlinear systems mostly target the systems with special structures or focus only on the control based on neural networks which are unsuitable for real-time control due to their computation complexity. It is thus necessary to find a new approach to real-time tracking control of time-varying nonlinear systems. In this paper, a control scheme based on multi-dimensional Taylor network (MTN) is proposed to achieve the real-time output feedback tracking control of multi-input multi-output (MIMO) non-affine nonlinear time-varying discrete systems relative to the given reference signals with online training. A set of ideal output signals are selected by the given reference signals, the optimal control laws of the system relative to the selected ideal output signals are set by the minimum principle, and the corresponding optimal outputs are taken as the desired output signals. Then, the MTN controller (MTNC) is generated automatically to fit the optimal control laws, and the conjugate gradient (CG) method is employed to train the network parameters offline to obtain the initial parameters of MTNC for online learning. Addressing the time-varying characteristics of the system, the back-propagation (BP) algorithm is implemented to adjust the weight parameters of MTNC for its desired real-time output tracking control by the given reference signals, and the sufficient condition for the stability of the system is identified. Simulation results show that the proposed control scheme is effective and the actual output of the system tracks the given reference signals satisfactorily.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 30 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): X. Cao, M.B. Saltik, S. Weiland〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Optimal Hankel norm model reduction for dynamical systems is of great significance in model-based simulation and design. For the class of linear time-invariant systems, it is among the few optimal reduction methods for which a prior error bound between the original system and its approximation is known. However, for descriptor systems, this optimal approximation technique no longer applies. In this paper, we propose several definitions of the Hankel operator for dynamical discrete-time descriptor systems. We investigate the implications of these definitions for the problem of optimal model approximation of descriptor systems in the sense of the Hankel norm. Novel reduction algorithms are derived for this class of systems with and without preservation of the DAE-index. The performance of the proposed methods is illustrated by numerical examples.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Ravi P. Agarwal, Qaisar Badshah, Ghaus ur Rahman, Saeed Islam〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The present work is devoted to study the asymptotic nature of a stochastic pine wilt disease model. Investigating the basic reproductive number, we proved that it has sharp threshold properties. The underlying system of stochastic differential equations is analyzed, and proper Lyapunov functionals are formulated to show the stability analysis. Adequate conditions are provided to study the extinction and permanence of the disease. Reducing infected individuals involved in a substance abuse is a challenging task therefore, using some control variables the stochastic optimality system, is obtained. Furthermore, for the authenticity of the obtained results numerical simulations are carried out at the end of the manuscript.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Emad S. Hassan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The multi-taper spectrum (MTS) estimator enjoys a relatively low computational complexity and high estimation accuracy making it an attractive method for spectrum sensing in cognitive radio (CR) networks. However, it is difficult to guarantee both detection and false alarm probabilities when its design is based on fixed threshold, especially when the noise power fluctuates due to channel conditions. In this paper, a new adaptive threshold method to guarantee both detection and false alarm probabilities for MTS based spectrum sensing is proposed. By means of estimating noise power and signal power, the decision of adaptive threshold is able to adapt the noise fluctuation and achieve efficient trade-off between detection and false alarm probabilities. A closed form expression for the adaptive threshold is derived for both additive white Gaussian noise (AWGN) channel and multipath fading channel. Several metrics are employed to compare the performance of the proposed adaptive threshold method with that of the fixed threshold methods such as: error decision probability, detection probability, false alarm probability and throughput. The obtained results show that the proposed method achieves better spectrum efficiency and high throughput in comparison with the conventional fixed and adaptive threshold methods presented in the literature.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Tianliang Zhang, Feiqi Deng, Weihai Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the finite-time stability and stabilization of linear discrete time-varying stochastic systems with multiplicative noise. Firstly, necessary and sufficient conditions for the finite-time stability are presented via a state transition matrix approach. Secondly, this paper also develops the Lyapunov function method to study the finite-time stability and stabilization of discrete time-varying stochastic systems based on matrix inequalities and linear matrix inequalities (LMIs) so as to Matlab LMI Toolbox can be used.The state transition matrix-based approach to study the finite-time stability of linear discrete time-varying stochastic systems is novel, and its advantage is that the state transition matrix can make full use of the system parameter informations, which can lead to less conservative results. We also use the Lyapunov function method to discuss the finite-time stability and stabilization, which is convenient to be used in practical computations. Finally, three numerical examples are given to illustrate the effectiveness of the proposed results.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Renming Yang, Liying Sun〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the finite-time robust control problem of a class of nonlinear time-delay systems with general form, and proposes some new delay-independent and delay-dependent conditions on the issue. First, by developing an equivalent form, the paper studies finite-time stabilization problem, and presents some delay-dependent stabilization results by constructing suitable Lyapunov functionals. Then, based on the stabilization results, we study the finite-time robust control problem for the systems, and give a robust control design procedure. Finally, the study of two illustrative examples shows that the results obtained of the paper work well in the finite-time stabilization and robust stabilization for the systems. It is shown that, by using the method in the paper, the obtained results do not contain delay terms, which can avoid solving nonlinear mixed matrix inequalities and reduce effectively computational burden. Moreover, different from existing finite-time results, the paper also presents delay-dependent sufficient conditions on the finite-time control problem for the systems.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Fang Guo, Yu Liu, Fei Luo, Yilin Wu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we mainly concentrate on the control issue of a variable length drilling riser under condition of unknown disturbances and output constraint. The studied flexible drilling riser system with variable length, variable tension, variable speed and restricted boundary output is essentially a nonlinear distributed parameter system. For achieving the vibration suppression and ensuring the boundary output within the constrained range, an appropriate control scheme with output signal barrier is put forward by integrating boundary control method, barrier Lyapunov function with finite-dimensional backstepping technique, where disturbance observer is employed for coping with the boundary disturbance. Moreover, the Lyapunov’s synthetic method is applied for the steadiness research of the studied flexible drilling riser system, and the simulations are presented to display the usefulness of proposed control scheme.〈/p〉〈/div〉

Description: 〈p〉Publication date: March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 4〈/p〉 〈p〉Author(s): Le Yin, Hui Gao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Auto-Regressive-Moving-Average with eXogenous input (ARMAX) models play an important role in control engineering for describing practical systems. However, ARMAX models can be non-realistic in many practical contexts because they do not consider the measurement errors on the output of the process. Due to the auto-regressive nature of ARMAX processes, a measurement error may affect multiple data entries, making the estimation problem very challenging. This problem can be solved by enhancing the ARMAX model with additive error terms on the output, and this paper develops a moving horizon estimator for such an extended ARMAX model. In the proposed method, measurement errors are modeled as nuisance variables and estimated simultaneously with the states. Identifiability was achieved by regularizing the least-squares cost with the ℓ〈sub〉2〈/sub〉-norm of the nuisance variables, which leads to an optimization problem that has an analytical solution. For the proposed estimator, convergence results are established and unbiasedness properties are also proved. Insights on how to select the tuning parameter in the cost function are provided. Because of the explicit modeling of output noise, the impact of a measurement error on multiple data entries can be estimated and reduced. Examples are given to demonstrate the effectiveness of the proposed estimator in dealing with additive output noise as well as outliers.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Yiwen Qi, Zheng Cao, Xianling Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is concerned with the decentralized event-triggered 〈em〉H〈/em〉〈sub〉∞〈/sub〉 control for switched systems subject to network communication delay and exogenous disturbance. Depending on different physical properties, the system state is divided into multiple communication channels and decentralized sensors are employed to collect signals on these channels. Furthermore, decentralized event-triggering mechanisms (DETMs) with a switching structure are proposed to determine whether the sampled data needs to be transmitted. In particular, an improved data buffer is presented which can guarantee more timely utilization of the sampled data. Then, with the proposed DETMs and data buffer, a time-delay closed-loop switched system is developed. After that, sufficient conditions are presented to guarantee the 〈em〉H〈/em〉〈sub〉∞〈/sub〉 performance of the closed-loop switched system by utilizing the average dwell time and piecewise Lyapunov functional method. Since the event-triggered instants and the switching instants may stagger with each other, the influence of their coupling on the 〈em〉H〈/em〉〈sub〉∞〈/sub〉 performance analysis is systematically discussed. Subsequently, sufficient conditions for designing the event-triggered state feedback controller gains are provided. Finally, numerical simulations are given to verify the effectiveness of the proposed method.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Maziar Ebrahimi Dehshalie, Mohammad B. Menhaj, Mehdi Karrari〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The goal of this paper is to propose an optimal fault tolerant control (FTC) approach for multi-agent systems (MASs). It is assumed that the agents have identical affine dynamics. The underlying communication topology is assumed to be a directed graph. The concepts of both inverse optimality and partial stability are further employed for designing the control law fully developed in the paper. Firstly, the optimal FTC problem for linear MASs is formulated and then it is extended to MASs with affine nonlinear dynamics. To solve the Hamilton-Jacobi-Bellman (HJB) equation, an Off-policy Reinforcement Learning is used to learn the optimal control law for each agent. Finally, a couple of numerical examples are provided to demonstrate the effectiveness of the proposed scheme.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Emre Çelik, Halil Gör〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Since Proportional + Integral + Derivative (PID) controller is still the workhorse in taking over the workload of process control systems, this article introduces a new design methodology toward improving the performance of such controller. After a PI control law with windup protection is given, it is combined with a derivative path employing a first-order low pass filter in an innovative way to develop a performant controller called PI + DF controller. In attempting to attain a high level of control performance, gains of this controller including proportional, integral, derivative and filter gains are tuned choosing the recently introduced Stochastic Fractal Search (SFS) algorithm owing to its superiority to many state-of-the-art algorithms considering convergence, accuracy and robustness. To evaluate the efficacy of SFS, Particle Swarm Optimization (PSO) is also applied to the case study. Furthermore, the presented SFS optimized PI + DF controller is compared to a recently reported control scheme through simulation and experimental tests on an identical DC servo system. After providing the stability proof, SFS tuned PI + DF controller is found to be the pioneer in exhibiting the most accurate speed response profile under complicated scenarios, which is followed by PSO tuned PI + DF controller and the existing control approach, respectively.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Wei Qian, Yanshan Gao, Yonggang Chen, Junqi Yang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper focuses on the stability analysis of systems with interval time-varying delay. A new augmented vector containing single and double integral terms is constructed and the corresponding Lyapunov functional with triple integral terms is introduced. In order to improve the estimating accuracy of the derivatives of the constructed Lyapunov functional, single integral inequalities and double integral inequalities via auxiliary functions are employed on the first step, then an extended relaxed integral inequality and reciprocally convex approach are further utilized to narrow the scaling room of the functional derivatives. As a result, some novel delay-dependent stability criteria with less conservatism are derived. Finally, numerical examples are provided to check the effectiveness of the theoretical results and the improvement of the proposed method over the existing works.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Yan Wu, Jim Braselton, Yao Jin, Adel El Shahat〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The bi-directionally coupled Lorenz systems are linked to the modeling of a coupled double loop thermosyphon system where the mass momentum and heat exchange are both considered. As the key parameters of the system, known as Rayleigh numbers, increase, the system of differential equations predicts typical flow dynamics in a thermosyphon from heat conduction to time-dependent chaos. In many applications including the thermosyphon systems, there are uncertainties associated with mathematical models such as unmodeled dynamics and parameter variations. Also, under the high heat environment for a thermosyphon, there exist external disturbances quantitatively linked to the Rayleigh numbers. All these sources constitute uncertainties to the dynamical system. Our objective is to design adaptive controllers to stabilize the chaotic flow in each thermosyphon loop with unknown system parameters and existence of uncertainties. The controllers consist of a proportional controller with an adaptive gain and a wavelet network that reconstructs the unknown functions representing the uncertainties. Explicit stability bounds and adaptive laws for the control parameters are obtained so that the coupled Lorenz systems are globally stabilized.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Marcelo Menezes Morato, Manh Quan Nguyen, Olivier Sename, Luc Dugard〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This article is concerned with the control of a Semi-Active suspension system of a 7DOF Full Vehicle model, equipped with four 〈em〉Electro Rheological〈/em〉 (〈em〉ER〈/em〉) dampers, taking into account their incipient dissipativity constraints. Herein, a real-time, fast, advanced control structure is presented within the Model Predictive Control framework for Linear Parameter Varying (〈em〉LPV〈/em〉) systems. The control algorithm is developed to provide a suitable trade-off between comfort and handling performances of the vehicle in a very limited sampling period (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si15.gif" overflow="scroll"〉〈mrow〉〈msub〉〈mi〉T〈/mi〉〈mi〉s〈/mi〉〈/msub〉〈mo〉=〈/mo〉〈mn〉5〈/mn〉〈mspace width="0.16em"〉〈/mspace〉〈mtext〉ms〈/mtext〉〈/mrow〉〈/math〉), in view of a possible realtime implementation on a real vehicle. The control structure is tested and compared to other standard fast control approaches. Full nonlinear realistic simulation results illustrate the overall good operation and behaviour of the proposed control approach.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Salman Ijaz, Lin Yan, Mirza Tariq Hamayun, Cun Shi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, an active fault tolerant control (AFTC) scheme is proposed for more electric aircraft (MEA) equipped with dissimilar redundant actuation system (DRAS). The effect of various fault/failure of hydraulic actuator (HA) on the system performance is analyzed in this work. In nominal condition, the state feedback control law is designed for primary control surfaces. In the presence of fault/failure of certain HA, control allocation (CA) scheme together with integral sliding mode controller (ISMC) is retrofitted with existing control law and engaged the secondary (redundant) actuators into the loop. A modified recursive least square (RLS) algorithm is proposed to identify the parametric faults in HA and to measure the effectiveness level of the actuator. In an event of failure of all HA’s in the system, electro hydraulic actuators (EHA) are taken in loop to bring the system back to its nominal operation. In order to stabilize the closed-loop dynamics of HA and EHA, fractional order controllers are designed separately for each actuator. Simulations on the lateral directional model of aircraft demonstrated the effectiveness of the proposed scheme as compared to the existing methods in the literature.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Magdi S. Mahmoud, Yuanqing Xia, Sixing Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A class of networked nonlinear control systems with norm-bounded uncertainties is presented in this paper. The class is represented by Takagi–Sugeno (T-S) fuzzy models with packet processing. The network loop delay is considered either as known delay or random delay. For the former case, we develop conditions that guarantee the robust asymptotic stability and state-feedback stabilization with strict dissipativity and cast the results in linear matrix inequality (LMI) framework. Next employing a probabilistic-based delay partitioning method to deal with random delay, we establish novel LMI criteria for strict dissipative stability analysis and feedback synthesis. The efficacy of the ensuing techniques is demonstrated by numerical solution of typical examples and Mont Carlo simulation.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Zhibao Song, Junyong Zhai〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is concerned with the problem of global finite-time stabilization via output feedback for a class of switched stochastic nonlinear systems whose powers are dependent of the switching signal. The drift and diffusion terms satisfy the lower-triangular homogeneous growth condition. Based on adding a power integrator technique and the homogeneous domination idea, output-feedback controllers of all subsystems are constructed to achieve finite-time stability in probability of the closed-loop system. Distinct from the existing results on switched stochastic nonlinear systems, the delicate change of coordinates are introduced for dominating nonlinearities. Moreover, by incorporating a multiplicative design parameter into the coordinate transformations, the obtained control method can be extended to switched stochastic nonlinear systems with nonlinearities satisfying the upper-triangular homogeneous growth condition. The validity of the proposed control methods is demonstrated through two examples.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Lei Zhang, Bin Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is devoted to existence and uniqueness of minimal mild super solutions to the obstacle problem governed by integro-partial differential equations. We first study the well-posedness and local Lipschitz regularity of 〈em〉L〈sup〉p〈/sup〉〈/em〉 solutions (〈em〉p〈/em〉 ≥ 2) to reflected forward-backward stochastic differential equations (FBSDEs) with jump and lower barrier. Then we show that the solutions to reflected FBSDEs provide a probabilistic representation for the mild super solution via a nonlinear Feynman–Kac formula. Finally, we apply the results to study stochastic optimal control/stopping problems.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 3〈/p〉 〈p〉Author(s): Zhengwei Ge, Feng Ding, Ling Xu, Ahmed Alsaedi, Tasawar Hayat〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the parameter estimation problems of multivariate equation-error autoregressive moving average systems. Firstly, a gradient-based iterative algorithm is presented as a comparison. In order to improve the computational efficiency and the parameter estimation accuracy, a decomposition-based gradient iterative algorithm is presented by using the decomposition technique. The key is to transform an original system into two subsystems and to estimate the parameters of each subsystem, respectively. Compared with the gradient-based iterative algorithm, the decomposition-based algorithm requires less computational efforts, and the simulation results indicate that this algorithm is effective.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Boumediène Chentouf, Nejib Smaoui〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is consecrated to the feedback stabilization of the rotating disk-beam system. The beam is assumed to be non-uniform and clamped at its left-end to the center of the disk where a torque control takes place, while a memory boundary control is acting at the right-end of the beam. First, the usual torque control is proposed, whereas the boundary control is designed by taking into account a special type of a memory phenomenon, as well as the dynamic features of the input. Sufficient conditions on the angular velocity of the disk and the memory term are derived to guarantee the existence and uniqueness of solutions of the system. Furthermore, the frequency domain method is utilized in order to achieve the exponential stability of the closed-loop system. The relevance of the theoretical outcomes is shown through several numerical simulations.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 26 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Hui Shang, Guangdeng Zong, Wenhai Qi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the asynchronous positive 〈em〉H〈/em〉〈sub〉∞〈/sub〉 filtering is addressed for positive Markov jump systems. The asynchrony between the filter’s and the system’s modes is described through a conditional probability matrix. Three distinct asynchronous positive filters named an upper-bounding filter, a lower-bounding filter and a weighted filter are built. Sufficient conditions are established such that the filtering error systems are positive and finite-time bounded with an 〈em〉H〈/em〉〈sub〉∞〈/sub〉 disturbance attenuation level. It is proved that the weighted filter has more flexibilities than the bounding filters since it can adjust the parameter 〈em〉θ〈/em〉 when estimating the given systems. Finally, the effectiveness of the theoretical results is validated through the fish’s population evolution example.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 26 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Zhao-Yan Li, Qiuqiu Fan, Longsuo Li, Yibo Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is concerned with the stability analysis of linear continuous-time delay-difference systems with multiple delays. Firstly, a new method for testing the 〈em〉L〈/em〉〈sub〉2〈/sub〉-exponential stability of the considered system is proposed, which is easier to use than the one in the existing literature. In view of the conservatism and the complexity of the obtained stability conditions in the existing literature, a complete Lyapunov-Krasovskii functional (LKF) is constructed by analyzing the relationship among the multiple delays. Sufficient conditions for both 〈em〉L〈/em〉〈sub〉2〈/sub〉-exponential stability and exponential stability are then derived based on the constructed LKFs, which are delay-independent. Exponential convergence rate for the considered system is also investigated by a new method, which is shown to be equivalent to the existing approach by using weighted LKFs. Robust stability under parameter uncertainties is also investigated. Numerical examples are provided to demonstrate the effectiveness and less conservativeness of the proposed method.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 26 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Qiankang Hou, Li Ma, Shihong Ding, Xiaofei Yang, Xiangyong Chen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Aiming at steering an underactuated surface vessel (USV) with a shortest distance and lowest fuel cost to sail along the predetermined paths, this paper investigates the straight-line path-following problem for the USV in the presence of the disturbance, including system uncertainties, parameter perturbations and external disturbance, etc. First of all, by assuming that the disturbance does not exist, a state-feedback controller is designed for the path-following system by using finite-time control technique. Considering the facts that the yaw velocity of USV is usually not easy to be detected and the disturbance heavily affects the performance of the path-following system, a composite control method is developed in the presence of the disturbance to further improve the control performance by combining the finite-time differentiator (FTD) and the state-feedback controller. Owing to the disturbance estimation ability of FTD, the disturbance can be well compensated in real time, which implies that the robustness property of the closed-loop path-following system under the composite control scheme can be significantly improved. Finally, the simulation results are presented to verify the feasibility and effectiveness of the proposed algorithms.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 26 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Syed Ali Ajwad, Tomas Ménard, Emmanuel Moulay, Michael Defoort, Patrick Coirault〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper deals with the leader-following consensus problem of multi-agent systems with the consideration that each agent can only transmit its position state to the neighbors at irregular discrete sampling times. In the proposed algorithm, a continuous-discrete time observer is designed for the continuous estimation of both position and velocity from the discrete position information of the neighbors. These estimated states are then used for designing a continuous control law which solves the leader-following consensus problem. Moreover, the dynamics of the leader is not fixed and can be controlled through an external input. The stability analysis has been carried out by employing the Lyapunov approach which provides sufficient conditions to tune the parameters according to the maximum allowable sampling period. The developed algorithm has been simulated and then tested on an actual multi-robot system consisting of three differential drive wheeled robots. Both simulation and hardware results validate the effectiveness of the control algorithm.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xuexin Feng, Youqing Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This work discussed the design of a sliding mode observer for the estimation of actuator faults in a Takagi-Sugeno fuzzy system with digital communication channel. Signals must be quantified before they enter the digital communication channel in network environments. In this work, the fuzzy sliding mode observer was used to offset the effects of quantization and uncertainty. The sliding mode observer can compensate for quantization errors, overcome uncertainty effects, and reconstruct fault vectors if the quantization density was 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si4.svg"〉〈mrow〉〈msqrt〉〈mn〉2〈/mn〉〈/msqrt〉〈mo linebreak="goodbreak"〉−〈/mo〉〈mn〉1〈/mn〉〈mo linebreak="goodbreak"〉〈〈/mo〉〈mi〉σ〈/mi〉〈mo linebreak="goodbreak"〉〈〈/mo〉〈mn〉1〈/mn〉〈/mrow〉〈/math〉 and a given linear matrix inequality had a feasible solution. Finally, a simulation was performed to verify the effectiveness of the proposed method.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Shenghuang He, Yuanqing Wu, Yanzhou Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the finite-time synchronization problem of complex networks subject to input delay. The time-varying sampling is required to be aperiodic, which implies that the difference of any two continuous sampling instants doesn’t exceed a given upper bound. Together with free-weighting matrix approach, a fresh Lyapunov functional is employed to establish a sufficient condition, solving the finite-time synchronization problem. On the other hand, the synchronization of complex networks with input time-varying delay within a given time interval is considered. In order to solve such a problem, sufficient conditions are obtained based on non-fragile control protocol, the Lyapunov-Krasovskii stability theory (LKST) and integral inequality. The finite-time stability of complex networks in the presence of delay input delay can be achieved. At last, the smaller conservatism and the effectiveness of the obtain theoretical result is exhibited through some numerical simulations.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 14〈/p〉 〈p〉Author(s): Michael Z. Q. Chen, David Wagg, James Lam, Mehdi Ahmadian, Malcolm C. Smith〈/p〉

Description: 〈p〉Publication date: Available online 10 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Linna Wei, Wu-Hua Chen, Shixian Luo〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this work, impulsive stabilization problems of discrete-time switched linear systems with time-varying delays are studied. The sequence of impulsive instants is nearly-periodic, i.e., it is close to a periodic impulse and the distance between them is an uncertain bounded term. A time-varying Lyapunov function is introduced to characterize the information of delays, switching signals and impulses, and a stability criterion LMI-based is obtained without any restrictions on the stability of the subsystems. Several design schemes of reduced-order/full-order impulsive controllers with or without time-varying delays are developed. Finally, three numerical examples are provided to illustrate the effectiveness of the established results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 12 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Feng Dai, Bin Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper deal with an optimal control problem for a haptotaxis model of solid tumor invasion by considering the multiple treatments of cancer (a combination of radiotherapy and chemotherapy). Firstly, we obtain the existence and uniqueness of weak solution for the controlled system with spatial dimensions 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si9.svg"〉〈mrow〉〈mi〉N〈/mi〉〈mo linebreak="goodbreak"〉=〈/mo〉〈mn〉1〈/mn〉〈mo〉,〈/mo〉〈mn〉2〈/mn〉〈mo〉,〈/mo〉〈mn〉3〈/mn〉〈/mrow〉〈/math〉 by applying the Leray-Schauder fixed point theorem and developing adapted a priori estimates. Subsequently, the existence of optimal pair are proved by means of the technique of minimizing sequence. Furthermore, we verify the Lipschitz continuity of control-to-state mapping based on some a priori estimates, hence derive the first-order necessary optimality condition and establish the optimality systems. Finally, the ringlike diffusion and aggregation patterns and the dynamics of tumor invasion as well as the optimal control strategies are presented numerically, which demonstrate that the optimal treatment strategies are capable of breaking the pattern formation, and preventing the tumor invading and metastasizing, even eliminating the tumor possibly. The results of this work improved and extended previous results partially.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 10 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Menghua Chen, Hamid Reza Karimi, Jian Sun〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The problem of finite time stability and synthesis is discussed for nonlinear discrete time-varying systems by using the T-S fuzzy model. To reduce the communication network resources, two adaptive event-triggered mechanisms (AETMs) are taken into consideration in sensor-to-observer (S/O) and observer-to-controller (O/C) channels. The thresholds of the AETMs are adjusted according to the estimation error rather than some fixed ones. Sufficient conditions for developing an observer-based time-varying control are obtained, which ensure the time-varying error system to be finite time stable and satisfy the 〈em〉H〈/em〉〈sub〉∞〈/sub〉 performance simultaneously. Moreover, using the singular value decomposition technique, recursive linear matrix inequalities conditions are obtained for computing the gains of the controller and observer. Finally, the superiority and applicability of the proposed method are demonstrated by examples.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Mengzhou Gao, Dongqin Feng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the problem of secure control for networked control systems (NCSs) under randomly occurring zero-value attacks (ROZVAs). Specifically, ROZVAs only offset the true signal without injecting obfuscated information or noises, and possess the minimum energy of the added malicious information. To protect system stability against ROZVA, randomly occurring integrity check protection (ROICP) is introduced which prevents malicious data injection with less energy cost than persistently occurring protection. Besides the random phenomena of ROZVA and ROICP, which are characterized by two mutually independent random variables obeying the Bernoulli distribution, the randomly occurring time delays caused by ROICP is also considered in system modelling. According to the built stochastic linear system model, security analysis of the NCS with ROICP subject to ROZVA is carried out and sufficient condition of stochastic stability is derived via a linear matrix inequality (LMI) approach. Based on the proposed condition, a compensation feedback controller is designed to facilitate system stability. Finally, simulation results show the effectiveness of the proposed method.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Qian Wang, Cong Wang, Qinghua Sun〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Time-to-failure (TTF) prediction is one of the most difficult problems in the area of prognostic and health management. In this paper, a new model-based TTF prediction scheme is proposed. Based on deterministic learning theory, a system dynamical pattern bank consisting of health, sub-health and fault patterns is established, and a set of estimators associated with the learned system patterns is used to generate average 〈em〉L〈/em〉〈sub〉1〈/sub〉 norms of system residuals. Then, a TTF prediction model is derived based on the system residual generator with a predefined failure pattern. Once the first predicting time is obtained according to the incipient fault detection scheme, the system TTF can be predicted by projecting the learned fault dynamics at the current time against the failure threshold. Finally, an incipient fault detection and TTF prediction (IFDTP) algorithm is implemented by combining the established bank, the first predicting time and the TTF model. The novelty of this paper lies in that the new TTF prediction scheme can provide a more accurate system failure time for nonlinear dynamical systems, and the effectiveness of the proposed IFDTP algorithm is illustrated by simulation studies.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Yueyuan Zhang, Cheng-Chew Lim, Fei Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents an active fault tolerant control scheme for discrete-time semi-Markov jump systems. The semi-Markov kernel approach and the finite sojourn time restriction are employed to obtain finite stability sufficient conditions for stability and stabilization. Semi-Markov processes are applied to model the faults occurrence of the actuators and the fault detection process. To guarantee the stability of the resulting closed loop system, an elapsed-time-dependent controller design method is applied. Finally, a numerical example and a vertical take-off and landing vehicle (VTOL) example are shown to illustrate the effectiveness and potential of the proposed design technique.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): A. Aziz Khater, Ahmad M. El-Nagar, Mohammad El-Bardini, Nabila M. El-Rabaie〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, an adaptive interval type-2 Takagi-Sugeno-Kang fuzzy logic controller based on reinforcement learning (AIT2-TSK-FLC-RL) is proposed. The proposed controller consists of an actor, a critic and a reward signal. The actor is represented by the IT2-TSK-FLC in which the antecedents and the consequents are interval type-2 fuzzy sets (IT2FSs) and type-1 fuzzy sets (T1FSs), respectively, which are named A2-C1. The critic is represented by a neural network, which approximates the optimal guaranteed cost in the control design to ensure the system stability for all admissible uncertainties and noise. The use of a reward signal to formalize the idea of a goal is one of the most distinctive features of RL. Thus, the proposed controller evolves in time as a result of the online learning algorithm. The parameters of the proposed controller are learned online based on the Lyapunov theorem to guarantee the stability, overcome the shortcomings of the gradient descent, such as the local minima and instability, and determine the learning rate of the IT2-TSK-FLC controller. Furthermore, the critic stability is discussed for determining the optimal learning rate. The proposed controller is applied to uncertain nonlinear systems to show its robustness in reducing the effect of system uncertainties and external disturbances and is compared to other controllers.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): K.E. Liang, LI Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the problem of exponential synchronization for inertial Cohen-Grossberg neural networks with time delays is studied. According to the concept of synchronization, a controlled response system is constructed to obtain the error systems. First, by introducing a directive Lyapunov functional, a sufficient condition is derived to ascertain the exponential synchronization of the drive and response systems based on feedback control. Moreover, by introducing a variable substitution, a sufficient condition is obtained to ensure the global exponential synchronization for the systems. Two sufficient conditions are feasible for the global exponential synchronization of the drive and response systems, and complement each other. Finally, the parameters were set for numerical simulation, two illustrative examples are provided to show the effectiveness of the obtained theoretical results, and the validity of the model was proved.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 17 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Jorge E. Ruiz-Duarte, Alexander G. Loukianov〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the error-feedback output tracking problem for discrete-time linear perturbed systems with arbitrary references and unknown disturbances is approximately solved. To obtain the approximated system state error, a dynamic estimator is designed using a state observer, based on the plant model and considering the tracking error as the system output. The proposed solution is based on the approximation of a discrete-time function, using various previous steps of itself. This approximation is used in the proposed observer to estimate the reference profile of the control input. Based on the estimated state error, a discrete-time sliding mode controller is then designed to achieve the approximate tracking of the arbitrary reference. The simulations show the effectiveness of the proposed control scheme.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 15 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Jiachang Wang, Yiheng Wei, Tianyu Liu, Ang Li, Yong Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper mainly investigates the issue of parameters identification for continuous time fractional order Hammerstein systems. When the commensurate order of linear part in system is prior information, two estimation algorithms are proposed to identify the parameters. Both methods use filters to obtain the derivative of the continuous time signal: one based on the Poisson filter and the other using the auxiliary model to construct the filter. Afterwards, the commensurate order update law is given, which contains the relationship between parameters and orders. In addition, due to the existence of fractional order terms, an irrational item will be introduced, and this paper gives a detailed mathematical derivation to discuss this issue. The effectiveness of proposed methods is demonstrated by the numerical simulations.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 15 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Tao Li, Ting Wang, Yaobo Yu, Shumin Fei〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this work, the design on static anti-windup compensator (SAWC) for a class of nonlinear systems with saturation constraint is presented, in which both state time-varying delay and input one are involved. First, by utilizing an augmented Lyapunov-Krasovskii functional (LKF), sector condition, and 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si8.svg"〉〈msub〉〈mi mathvariant="bold-script"〉L〈/mi〉〈mn〉2〈/mn〉〈/msub〉〈/math〉 gain reduction for exogenous input, a sufficient condition on local stability is presented in terms of linear matrix inequalities (LMIs), which is later extended to the global stability issue. During the discussions, an improved dynamical Lyapunov method is initially proposed and it can fully utilize the individual and mutual information on both state and input delays. Especially, some effective techniques are utilized to given more tighter estimations on the LKF’s derivatives. In all, these treatments above can result in much less conservatism. Finally, some comparisons and simulations are presented in two numerical examples under the proposed SAWC.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 15 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Chengfei Yue, Feng Wang, Xibin Cao, Qiang Shen, Xueqin Chen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The robust fault-tolerant (FT) attitude tracking control problem with guaranteed prescribed performance is addressed in this paper. We consider the actuator fault, misalignment, sensor fault and external disturbance simultaneously and incorporate the 〈em〉L〈/em〉〈sub〉2〈/sub〉 control allocation (CA) method to minimize the use of faulty actuators. To guarantee the prescribed performance such as the steady-state tracking error, convergence rate, as well as overshoot and undershoot, the constrained quaternion error is transformed to an unconstrained state, whose stabilization is proven to be sufficient and necessary to guarantee the performance requirement. With the utilization of the transformed state and the compromised angular velocity error suffering from gyro faults, a novel adaptive sliding mode FT control law with CA is developed. Ultimate uniform boundedness of the compromised angular velocity error and transformed state is ensured to satisfy the specified tracking performance. Numerical simulations are conducted on a rigid spacecraft to illustrate the efficiency of the proposed robust FT control law.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 14 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Gang Wang, Yunfeng Ji, Chaoli Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is devoted to tracking control for a class of strict-feedback time-varying nonlinear systems with unknown control directions. Currently, most existing control methods for strict-feedback nonlinear systems can realize asymptotic tracking while neglecting the transient performance; or they can guarantee the preassigned transient performance, but merely ultimately bounded tracking error is reached. By introducing smooth compensating terms in a function form of tracking errors, an innovative control algorithm is proposed that can ensure preassigned bounds of overshoot and convergence rate without 〈em〉a priori〈/em〉 knowledge of control directions while achieving asymptotic tracking and global uniform boundedness of all the closed-loop signals. Furthermore, the adaptive 〈em〉σ〈/em〉-modification control algorithm for the parameter estimates is developed, which renders smaller parameter estimates and thus results in lower shocks on the control input without compromising the preassigned transient performance and asymptotic tracking convergence. The proposed control algorithms obviate the need for analytic calculation of the partial derivatives of the stabilizing functions (virtual controllers) that is typically employed in controlling of strict-feedback systems, and are therefore more easily derived and implemented. Simulations are provided to verify the theoretical findings.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 2 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Fan Yang, Zhou Gu, Jun Cheng, Jinliang Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper addresses the issue of event-driven state-feedback controller design for networked switched systems in the finite-time sense. At the plant design level, the synchronism between switched systems and the corresponding controllers is guaranteed by introducing a mode-decision unit at the actuator side. Through intensive time interval analysis approach, the switched system, the event-triggered scheme, transmission delays and cyber attacks are unified into a new closed control system. Sufficient conditions are developed to ensure the networked switched system finite-time bounded by constructing a proper Lyapunov function. Then, the design methods for switched sub-controllers, optimal event-triggered parameters and restrictive average dwell-time switching law are presented. It is worth pointing out that the main results not only contribute to optimize limited network resources but also improve the system security level, which is validated through an illustrative example of a boost converter circuit.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 24 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Valiollah Ghaffari〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A composite nonlinear feedback tracking control is mainly designed via the linear matrix inequality approach in the time-delay nonlinear systems. For achieving this purpose, the composite nonlinear feedback control design is firstly formulated in the nonlinear systems with time-delay. Then, a sufficient stability condition will be addressed in terms of the linear matrix inequality feasibility checking. Therefore, a stabilizing composite nonlinear feedback control policy can be obtained with solving of the linear matrix inequality. A quadratic cost function is considered as a performance index for optimal tuning of the composite nonlinear feedback control. A minimization problem subject to some linear matrix inequality constraints would be subsequently suggested to the composite nonlinear feedback control tuning. The proposed control method is numerically simulated in two time-delay dynamical systems. The effectiveness of the suggested control law will be shown in comparing with the existing control techniques.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 5 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Jinnan Luo, Wenhong Tian, Shouming Zhong, Kaibo Shi, Daixi Liao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, the non-fragile asynchronous reliable sampled-data control for uncertain Takagi–Sugeno fuzzy systems with Bernoulli distribution is addressed. The system involves both the randomly occurring uncertainties of parameters in the fuzzy system model and randomly occurring gain perturbations of the controller. By introducing three stochastic variables, a new model structure satisfying Bernoulli distribution is formulated to describe the system and the controller. The main purpose of this study is to design the non-fragile asynchronous reliable sampled-data controller such that the considered system is finite-time bounded and possesses finite-time mixed 〈em〉H〈/em〉〈sub〉∞〈/sub〉 and passive performance. Based on an improved Lyapunov-Krasovskii functional, newly bounding inequalities and stochastic processing method, new conditions satisfying the required result are derived for the uncertain fuzzy systems in terms of linear matrix inequalities. Moreover, a modified non-fragile asynchronous reliable sampled-data controller is designed. Finally, two numerical examples are given to demonstrate the effectiveness of the presented results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 4 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Jiangbo Yu, Yan Zhao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we investigate the global robust stabilization problem for a class of uncertain chained-form nonholonomic systems. Remarkably, the studied system allows the nonlinear dynamic uncertainties. Characterizing the system of dynamic uncertainties via Sontag’s input-to-state stability (ISS) and ISS-Lyapunov function, we present a novel robust stabilization scheme via output feedback. The input-state scaling transformation is employed in this procedure to design a discontinuous time-invariant control law. A technical lemma is proposed in this paper to handle the dynamic uncertainties combining with the changing supply rates technique. Moreover, a switching control strategy based on the state magnitude is applied to get around the smooth stabilization burden associated with nonholonomic systems. The simulation results illustrate the efficacy of the presented algorithm.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 4 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Eva Žáčeková, Matej Pčolka, Michael Šebek〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the task of ensuring sufficiently excited data for the subsequent re-identification of a model used within the model predictive control framework is tackled. It introduces two algorithms that are developed specifically for zone MPC for systems with external disturbances. Both of them work in two steps and build on the original zone MPC solution. The trade-off between the data informativeness and degradation of the control performance is given by a user-defined threshold for the performance degradation. Moreover, a new optimization criterion quantifying data informativeness is introduced. The proposed algorithms are described in detail and their theoretical properties are discussed. Two different verification scenarios are presented, the first one with an artificial example and the second one considering a real-life building climate control task using a high-fidelity testbed model. The results show that they significantly outperform the classic zone MPC in data informativeness while maintaining acceptable zone violation and energy consumption.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 5 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Lu Liu, Shuo Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, a novel fractional-order partial pole assignment (FPPA) control algorithm is proposed for systems with time-delay. The FPPA control algorithm is essentially an extension of the original pole assignment, which could change undesired pole locations into desired pole locations. The presented control scheme can be used on open loop poorly damped or unstable systems, which is superior to most other time-delay compensation schemes. The discussion on choosing desirable pole locations is presented based on stability and resonance conditions in the frequency domain. The controlled system is also studied in the time domain based on different transient performance indicators, namely overshoot, settling time, and rising time. In addition, the parameters of the proposed FPPA control algorithm are tunable, thus the control scheme can be used to satisfy different control requirements. Simulation results of stable and unstable fractional-order plants with time-delay are shown to verify the effectiveness and practicability of the FPPA control algorithm.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 9 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Jing Duan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Since the risk of loan defaulting in peer-to-peer (P2P) lending is notoriously difficult to evaluate, a deep neural network-based decision-making approach is proposed in this work for more effective assessment of P2P lending risks. Although normally a dozen features were used for neural network modeling in previous studies carried out by other researchers on similar topics, more comprehensive features including both numeric and categorical ones (e.g. home ownership and purpose of loan), are considered in this work for improved modeling. Since categorical data cannot be used directly as the input of neural networks, they are converted to numerical data using one-hot encoding function. The deep neural network (DNN) used in this work is a multilayer perceptron (MLP) with three hidden layers trained by the back-propagation algorithm. In empirical analysis, the loan data issued by the Lending Club through 2007-2015 are classified into three classes, i.e. safe loan, risky loan and bad loan using TensorFlow. The training and test data sets consist of 221,712 and 55,428 data observations, respectively. Since most of the data belong to the class of safe loan, Synthetic Minority Over-Sampling Technique (SMOTE) is used to improve the DNN prediction accuracy. It is shown that with the proposed approach the test data are classified at an accuracy of 93%, which is much higher than the predication accuracy of 75% obtained using MLP with only one hidden layer.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 7 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Huaqing Li, Hao Zhang, Zheng Wang, Yifan Zhu, Qi Han〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper considers solving a class of optimization problems over a network of agents, in which the cost function is expressed as the sum of individual objectives of the agents. The underlying communication graph is assumed to be undirected and connected. A distributed algorithm in which agents employ time-varying and heterogeneous step-sizes is proposed by combining consensus of multi-agent systems with gradient tracking technique. The algorithm not only drives the agents’ iterates to a global and consensual minimizer but also finds the optimal value of the cost function. When the individual objectives are convex and smooth, we prove that the algorithm converges at a rate of 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"〉〈mrow〉〈mi〉O〈/mi〉〈mo〉(〈/mo〉〈mn〉1〈/mn〉〈mo〉/〈/mo〉〈msqrt〉〈mi〉t〈/mi〉〈/msqrt〉〈mo〉)〈/mo〉〈/mrow〉〈/math〉 if the homogeneous step-size does not exceed some upper bound, and it accelerates to 〈em〉O〈/em〉(1/〈em〉t〈/em〉) if the homogeneous step-size is sufficiently small. When at least one of the individual objectives is strongly convex and all are smooth, we prove that the algorithm converges at a linear rate of 〈em〉O〈/em〉(〈em〉λ〈sup〉t〈/sup〉〈/em〉) with 0 〈 〈em〉λ〈/em〉 〈 1 even though the step-sizes are time-varying and heterogeneous. Two numerical examples are provided to demonstrate the efficiency of the proposed algorithm and to validate the theoretical findings.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 9 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xiaobo Chi, Xinchun Jia, Fangqin Cheng, Maohong Fan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies networked 〈em〉H〈/em〉〈sub〉∞〈/sub〉 filtering for Takagi–Sugeno fuzzy systems with multi-output multi-sensor asynchronous sampling. Different output variables in a dynamic system are sampled by multiple sensors with different sampling rates. To estimate the signals of such a system, a continuous multi-rate sampled-data fusion method is proposed to design a novel networked filter. By considering a class of decentralized event-triggered transmission schemes, multi-channel network-induced delays, and the updating modes of the MOMR sampled-data, a networked jumping fuzzy filter is proposed to estimate system signals based on the transmitted multi-rate sampled-data of fuzzy system and the multi-rate sampled states of filter, and the jumping among filter modes is governed by a Markov process which depends on the arrival times of sampled output sub-vectors. To deal with asynchronous membership functions, the networked fuzzy filtering system is modeled as an uncertain fuzzy stochastic system with membership function deviation bounds. Based on stability and 〈em〉H〈/em〉〈sub〉∞〈/sub〉 performance analysis, several membership-function-dependent conditions are presented to co-design the event-triggered transmission schemes and the fuzzy filter such that the filtering error system is robustly mean-square exponentially stable with a prescribed 〈em〉H〈/em〉〈sub〉∞〈/sub〉 attenuation level. Finally, the improvement in estimation performance and comparison with the existing filtering methods are discussed through simulation examples.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 7 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Ming-Zhe Dai, Feng Xiao, Bo Wei〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the consensus problem of multi-agent systems by event- and self-triggered control. An event-triggered algorithm with periodic event detection and relative state measurements is designed to determine all event times. Furthermore, a self-triggered control algorithm with periodic event detection and quantization is proposed to further reduce resource consumption. In the proposed control strategies, only relative state information, or called edge information, is utilized by controllers, and all edge state information incident to each agent is processed together. The results are illustrated by two numerical experiments.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 20 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Shaoying Wang, Xuegang Tian, Huajing Fang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper mainly focuses on the event-based state and fault estimation problem for a class of nonlinear systems with logarithmic quantization and missing measurements. The sensors are assumed to have different missing probabilities and a constant fault is considered here. Different from a constant threshold in existing event-triggered schemes, the threshold in this paper is varying in the state-independent condition. With resort to the state augmentation approach, a new state vector consisting of the original state vector and the fault is formed, thus the corresponding state and fault estimation problem is transmitted into the recursive filtering problem. By the stochastic analysis approach, an upper bound for the filtering error covariance is obtained, which is expressed by Riccati difference equations. Meanwhile, the filter gain matrix minimizing the trace of the filtering error covariance is also derived. The developed recursive algorithm in the current paper reflects the relationship among the upper bound of the filtering error covariance, the varying threshold, the linearization error, the probabilities of missing measurements and quantization parameters. Finally, two examples are utilized to verify the effectiveness of the proposed estimation algorithm.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 15 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Hashim A. Hashim, Lyndon J. Brown, Kenneth McIsaac〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper formulates the pose (attitude and position) estimation problem as nonlinear stochastic filter kinematics evolved directly on the Special Euclidean Group 3 (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si18.gif" overflow="scroll"〉〈mrow〉〈mi mathvariant="double-struck"〉SE〈/mi〉〈mrow〉〈mo stretchy="true"〉(〈/mo〉〈mn〉3〈/mn〉〈mo stretchy="true"〉)〈/mo〉〈/mrow〉〈/mrow〉〈/math〉). This work proposes an alternate way of potential function selection and handles the problem as a stochastic filtering problem. The problem is mapped from 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si18.gif" overflow="scroll"〉〈mrow〉〈mi mathvariant="double-struck"〉SE〈/mi〉〈mrow〉〈mo stretchy="true"〉(〈/mo〉〈mn〉3〈/mn〉〈mo stretchy="true"〉)〈/mo〉〈/mrow〉〈/mrow〉〈/math〉 to vector form, using the Rodriguez vector and the position vector, and then followed by the definition of the pose problem in the sense of Stratonovich. The proposed filter guarantees that the errors present in position and Rodriguez vector estimates are semi-globally uniformly ultimately bounded (SGUUB) in mean square, and that they converge to small neighborhood of the origin in probability. Simulation results show the robustness and effectiveness of the proposed filter in presence of high levels of noise and bias associated with the velocity vector as well as body-frame measurements.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Hamed Jabbari Asl, Tatsuo Narikiyo, Michihiro Kawanishi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, we addressed the problem of design of high-performance tracking controller for uncertain systems described by the Euler-Lagrange formulation. The main objective was to combine the advantages of the robust integral of the sign of the error (RISE) controller with those of the prescribed performance (PP) controller. In particular, we aimed to obtain asymptotic tracking for the uncertain systems through a continuous control command while ensuring the transient performance. Two controllers were developed. First, the PP property was injected into the RISE controller assuming no constraint on the actuation amplitude existed, and then this property was incorporated into the saturated RISE controller. The performance of the proposed controllers was validated through experimental and simulation tests.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xiaohang Li, Weidong Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes a method on overall fault estimation and fault-tolerant control for a type of Markovian jump systems owning generally uncertain transition rates. We first extend the dimension of the original system by assembling the actuator fault and sensor fault into the state vector, and then develop a novel observer to estimate both the actuator fault and sensor fault in a simultaneous way, as well as to ensure the resulting estimated error dynamic system being stochastically 〈em〉H〈/em〉〈sub〉∞〈/sub〉 finite-time bounded. Based on the estimated states and actuator fault, a robust finite-time fault-tolerant controller is proposed to allow the closed-loop system to be finite-time bounded. With the aid of the stochastic Lyapunov function, sufficient conditions of the designed observer and fault-tolerant controller are derived in terms of linear matrix inequalities, making the problem tractable. Finally, an example is brought to testify the feasibility and efficiency of the proposed method.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Min Li, Caohui Mao, Ming-Feng Ge, Jinqiang Gan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In precision motion systems, well-designed feedforward control can effectively compensate for the reference-induced error. This paper aims to develop a novel data-driven iterative feedforward control approach for precision motion systems that execute varying reference tasks. The feedforward controller is parameterized with the rational basis functions, and the optimal parameters are sought to be solved through minimizing the tracking error. The key difficulty associated with the rational parametrization lies in the non-convexity of the parameter optimization problem. Hence, a new iterative parameter optimization algorithm is proposed such that the controller parameters can be optimally solved based on measured data only in each task irrespective of reference variations. Two simulation cases are presented to illustrate the enhanced performance of the proposed approach for varying tasks compared to pre-existing results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Nana Yang, Junmin Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the distributed consensus problems of leader-follower multi-agent systems with unknown time-varying coupling gains and parameter uncertainties are investigated, and the fully distributed protocols with the adaptive updating laws of periodic time-varying parameters are designed by using repetitive learning control. By virtue of algebraic graph theory, Barbalat’s lemma and an appropriate Lyapunov-Krasovskii functional, it is shown that each follower agent can track the leader asymptotically even though the dynamic of the leader is unknown to any of them, i.e., the global asymptotic consensus can be achieved. A simulation example is given to illustrate the feasibility and efficiency of the proposed protocols.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 22 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Lijuan Zha, Jinliang Liu, Jinde Cao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The distributed event-triggered secure consensus control is discussed for multi-agent systems (MASs) subject to DoS attacks and controller gain variation. In order to reduce unnecessary network traffic in communication channel, a resilient distributed event-triggered scheme is adopted at each agent to decide whether the sampled signal should be transmitted or not. The event-triggered scheme in this paper can be applicable to MASs under denial-of-service (DoS) attacks. We assume the information of DoS attacks, such as the attack period and the consecutive attack duration, can be detected. Under the introduced communication scheme and the occurrence of DoS attacks, a new sufficient condition is achieved which can guarantee the security consensus performance of the established system model. Moreover, the explicit expressions of the triggering matrices and the controller gain are presented. Finally, simulation results are provided to verify the effectiveness of the obtained theoretical results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 20 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Yunliang Wei, Guo-Ping Liu, Guangdeng Zong, Hao Shen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the problem of composite control for a class of uncertain Markovian jump systems (MJSs) with partial known transition rates, multiple disturbances and actuator saturation. Compared with the existing results, a novel robust composite control scheme is put forward by virtue of adaptive neural network technique. For MJSs, the partial unknown information on transition rates and the actuator saturation influence the design of disturbance observer and the robust 〈em〉H〈/em〉〈sub〉∞〈/sub〉 controller. Firstly, without taking account of external disturbances, the network reconstruction error and saturation, a novel robust adaptive control strategy is established to ensure that all the signals of the closed-loop system are asymptotically bounded in mean square. Secondly, the solvability condition for ensuring the robust 〈em〉H〈/em〉〈sub〉∞〈/sub〉 performance is given by using a modified adaptive law, where the saturation is treated as a disturbance-like signal. Finally, the simulations for a numerical example and an application example are performed to validate the effectiveness of the proposed results.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute, Volume 356, Issue 7〈/p〉 〈p〉Author(s): Tousif Khan Nizami, Arghya Chakravarty, Chitralekha Mahanta〈/p〉

Description: 〈p〉Publication date: Available online 5 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): C. Edwards, Y. Shtessel〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes a new Continuous Adaptive HOSM control algorithm. The key advantage of the adaption scheme is that it does not require knowledge of the bounds on the matched uncertainty, and the gains themselves are not conservatively overestimated by the adaption scheme – which helps mitigate the problem of chattering. Compared with earlier work, two variable parameters are allowed to adapt and this facilitates much better self-tuning capabilities and improved closed-loop performance.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 5 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): F. Palacios-Quiñonero, J. Rubió-Massegú, J.M. Rossell, H.R. Karimi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Distributed multi-actuator systems can provide effective solutions for mitigating the vibrational response of large structures. In this paper, we present a computational strategy to design inerter-based multi-actuation systems for the seismic protection of adjacent structures. The proposed approach allows considering both interstory and interbuilding Tuned Mass-Inerter Damper (TMID) actuators, and aims at simultaneously reducing the vibrational response of the individual buildings and avoiding the interbuilding impacts. The tuning procedure is based on an 〈em〉H〈/em〉〈sub〉∞〈/sub〉 cost-function and uses a constrained global-optimization solver to compute parameter configurations with high-performance characteristics. To illustrate the main features of this work, two different Tuned Inerter Damper (TID) multi-actuator schemes are considered for the seismic protection of a particular multi-story two-building system. A multi-actuator Tuned Mass Damper (TMD) system is also designed and is taken as a reference in the performance assessment. The obtained results demonstrate the flexibility and effectiveness of the proposed design methodology, and clearly show the superior performance and robustness of the TID actuation systems.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 22 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Na Lin, Ronghu Chi, Biao Huang, Zhongsheng Hou〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this article, a nonlinear iterative learning controller (NILC) is developed using an iterative dynamic linearization (IDL) and a parameter iterative learning identification technique. First, the ideal NILC is transformed into a linear parameterized form by using a controller-oriented compact form IDL (controller-CFIDL) technique. Then an iterative learning identification approach is presented for tuning the parameters of the proposed controller using real-time I/O data. For the sake of analysis, a linear data model of the nonlinear plant is obtained by using the system-oriented IDL technology and a corresponding system parameter identification algorithm is developed in iteration domain. The convergence analysis is provided for the dynamically linearized nonlinear and nonaffine discrete-time system. The results are further extended by using a controller-oriented partial form iterative dynamic linearization (controller-PFIDL) method to gain a higher-order NILC utilizing additional control information from previous iterations. Simulations of two examples show the effectiveness of the proposed methods.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Bao-Lin Zhang, Zhihui Cai, Shouwan Gao, Gong-You Tang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is concerned with the problem of delayed proportional-integral control of an offshore platform subject to self-excited nonlinear hydrodynamic force. By using current and distributed delayed states, a delayed proportional-integral controller is designed to stabilize the offshore platform. Under such a controller, the closed-loop system of the offshore platform is modeled as a nonlinear system with discrete and distributed delays, which allows us to employ the Lyapnov–Krasovskii functional method to analyze its asymptotic stability. Since an affine Wirtinger-based inequality is exploited to estimate the derivative of the Lyapunov–Krasovskii functional, a new stability criterion for the closed-loop system is derived, based on which, suitable control gains can be designed provided that a set of linear matrix inequalities are feasible. It is found through simulation results that the proposed control scheme can improve the control performance remarkably. Moreover, (i) compared with the existing delay-free controllers, the proposed controller can reduce the required control force and the oscillation amplitudes of the platform significantly; and (ii) compared with several delayed controllers, the proposed controller requires less control cost.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Mingxi Ai, Yongfang Xie, Shiwen Xie, Fanbiao Li, Weihua Gui〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Due to the unknown system structure of the froth flotation process and frequent fluctuations in production conditions, design of control strategy is a challenging problem. As a result, manual operation is still widely applied in practice by observing froth image feature. However, since the manual observation is subjective and the production conditions are time-varying, the manual operation cannot make decisions quickly and accurately. In this paper, a data-driven-based adaptive fuzzy neural network control strategy is developed to implement the automatic control of the antimony flotation process. The strategy is composed of fuzzy neural network (FNN) controllers, a data-driven model, and an on-line adaptive algorithm. The FNN is constructed to derive the control laws of the reagent dosages. The parameters of the FNN controllers are tuned by gradient descent algorithm. To obtain the real-time error feedback information, the data-driven model is established, which integrates the long short term memory (LSTM) network and radial basis function neural network (RBFNN). The LSTM network is utilized as a primary model, and the RBFNN is used as an error compensation model. To handle the challenges of the frequent fluctuations in the production conditions, the on-line adaptive algorithm is proposed to tune the parameters of the FNN controllers. Simulations and experiments are carried out in a real-world antimony flotation plant in China. The results demonstrate that the proposed adaptive fuzzy neural network control strategy produces better control performance than the other two existing methods.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 19 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Chaoxu Mu, Qian Zhao, Zhongke Gao, Changyin Sun〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates a Q-learning scheme for the optimal consensus control of discrete-time multiagent systems. The Q-learning algorithm is conducted by reinforcement learning (RL) using system data instead of system dynamics information. In the multiagent systems, the agents are interacted with each other and at least one agent can communicate with the leader directly, which is described by an algebraic graph structure. The objective is to make all the agents achieve synchronization with leader and make the performance indices reach Nash equilibrium. On one hand, the solutions of the optimal consensus control for multiagent systems are acquired by solving the coupled Hamilton-Jacobi-Bellman (HJB) equation. However, it is difficult to get analytical solutions directly of the discrete-time HJB equation. On the other hand, accurate mathematical models of most systems in real world are hard to be obtained. To overcome these difficulties, Q-learning algorithm is developed using system data rather than the accurate system model. We formulate performance index and corresponding Bellman equation of each agent 〈em〉i〈/em〉. Then, the Q-function Bellman equation is acquired on the basis of Q-function. Policy iteration is adopted to calculate the optimal control iteratively, and least square (LS) method is employed to motivate the implementation process. Stability analysis of proposed Q-learning algorithm for multiagent systems by policy iteration is given. Two simulation examples are experimented to verify the effectiveness of the proposed scheme.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 11 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Xudong Wang, Zhongyang Fei, Zhenhua Wang, Xinyu Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper is concerned with the event-triggered fault estimation and fault-tolerant control for continuous-time dynamic systems subject to system fault and external disturbance under network environment. Firstly, based on the event-triggered sampling, a fault diagnosis observer is constructed to estimate both the system state and the system fault simultaneously, and a multi-objective constraint is established to guarantee the estimation accuracy. Based on the estimated system state and fault signal, a fault-tolerant controller is proposed to compensate the influence of occurred faults and maintain the system performance. The event-triggered scheme and the fault-tolerant controller are co-designed to guarantee the required performance of faulty system and reduce the consumption of communication resources. Finally, simulation results of an F-404 aircraft engine system are provided to demonstrate the effectiveness of the proposed method.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 6 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Biao Ma, Yulong Liu, Xiaoxiang Na, Yahui Liu, Yiyong Yang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Shared control structure is beneficial to steering controller design of intelligence vehicles, and human-machine goal consistency is a key prerequisite for shared control. However, the goal consistency is usually given and cannot be changed, and the steering controller in low goal consistency, which directly affect the vehicle performance in case of emergency, has not been sufficiently investigated. This paper proposes a shared steering controller for path-following task based on Nash game strategy and steer-by-wire system considering different human-machine goal consistency. The driver-automation interactive path-following task is modeled by non-cooperative MPC, and authority weight of lateral displacement is used to balance the control objectives of the driver and automation. Human-machine goal consistency is determined by the driver and the automation controller steering angle. Aimed at different goal consistencies, a continuous authority weight adjustment algorithm is designed to ensure correct path following. This is especially true in low consistency in this study, when four driving modes are given to meet the different demand for control power. Simulations and hard-in-loop tests are conducted to verify the proposed control algorithm and the results show that it can perform the path-following task irrespective of human-machine goal consistency.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 2 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Hui Tian, Yanfang Hou〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Set stabilization of probabilistic Boolean control networks (PBCNs) is investigated in this paper and some interesting results are derived. The main results consist of three parts. (1) A definition of set stabilizability with probability one by closed-loop control is proposed for PBCNs, which is not a natural extension from deterministic Boolean control networks to PBCNs due to the random feature of PBCNs. (2) A necessary and sufficient set stabilizability condition is provided for PBCNs. (3) An algorithm for designing a state feedback controller is developed. It is guaranteed that all designed controllers can stabilize a PBCN to a given subset with probability one. The design method is constructive, so it is convenient to use this method in practical application. The results derived above are fundamental and important, since based on them many problems about PBCNs can be solved, for example partial stabilization, synchronization, and so on. Finally, a practical example is employed to show the effectiveness of our results.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Zong-Yao Sun, Cheng-Qian Zhou, Chih-Chiang Chen, Qinghua Meng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper focuses on the problem of finite-time stabilization for a class of high-order nonlinear systems with output constraint and zero dynamics. The systems under investigation possess two remarkable features: the output is restricted in a pre-specified region arising from the demand of practical operation, and inherent nonlinearities include nonlinear growth rate of high-order and low-order together with unmeasurable dynamic uncertainties. This paper proposes a continuous controller by means of a new tangent function and a serial of nonnegative integral functions with sign functions, and the controller ensures the adjustability of convergent speed of system state, which is faster than the counterpart of traditional finite-time stabilizers. The novelty is attributed to a perspective to applying the fast finite-time stability in partial state feedback control design in the case when the output is restricted. Finally, a numerical example is presented to demonstrate the effectiveness of the theoretical result.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Biao Wang, Jun-e Feng, Min Meng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the detectability problem of discrete event systems (DESs), and devotes to providing a synthetical method to cope with multiple cases, including (partial) event observation and/or partial state observation. By using the semi-tensor product method, two equivalent types of algebraic expressions are presented for DESs, based on which reachability of DESs is investigated in detail and a new tool called detection matrix is defined. Then, four matrix-based necessary and sufficient conditions are derived for checking different kinds of detectability. Finally, for better presentation, two examples are shown to demonstrate that the theoretical results are efficient.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 20 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Yuanqing Yang, Baocang Ding, Zuhua Xu, Jun Zhao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper addresses the output feedback model predictive control (OFMPC) of the constrained polytopic uncertain system in the presence of bounded state and output disturbances. The controller is designed in such a way that the unmeasurable state of the real system is bounded by the tube whose center is the estimated state of the disturbance-free (reference) model. The infinite-horizon reference control sequence is parameterized as a free control move followed by an output feedback law based on the reference state observer. By applying the OFMPC approach, the reference model is asymptotically stable so that robust stability of the real disturbed system is guaranteed. A numerical example is provided to illustrate the effectiveness of the proposed technique.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 20 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Cai-Cheng Wang, Guang-Hong Yang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the event-triggered decentralized control problem for interconnected nonlinear systems with input quantization is investigated. A state observer is constructed to estimate the unmeasurable states, and the state-dependent interconnections are accommodated by presenting some smooth functions. Then by employing backstepping technique and neural networks (NNs) approximation capability, a novel decentralized output feedback control strategy and an event-triggered mechanism are designed simultaneously. It is proved through Lyapunov theory that the closed-loop system is stable and the tracking property of all subsystems is guaranteed. Finally, the effectiveness of the proposed scheme is illustrated by an example.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 28 February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Hongbo Pang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies vector incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain and incremental stability for switched nonlinear systems using individual incremental gains and multiple storage functions. Firstly, a vector incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain concept for switched nonlinear systems is proposed. Each subsystem is not required to have incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain, but it has its own incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain and the related storage function, when it is active. The transformation of “energy” from the active subsystem to each inactive subsystem is characterized by cross-supply rates. Then, we show that a switched nonlinear system who has vector incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain can be incrementally stabilized under some constraints on the energy change of inactive subsystems. Secondly, a state-dependent switching law is designed to achieve vector incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain, even if each subsystem does not have incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain in the classic sense. Thirdly, each switched system is not required to have vector incremental 〈em〉L〈/em〉〈sub〉2〈/sub〉-gain, but the feedback interconnection of switched nonlinear systems is incrementally stabilized by the design of a composite switching law. The switching law allows the two switched systems switch asynchronously. Two examples are provided to verify the effectiveness of the proposed method.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Tao Wen, Quanbo Ge, Xinan Lyu, Lei Chen, Costas Constantinou, Clive Roberts, Baigen Cai〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉As a typical railway Cyber-physical System (CPS), radio-based train control systems have been playing an increasingly important role in rail transit. The engaged network, Global System for Mobile Communications for Railway (GSM-R), which is an out-dated wireless communication technology, will be decommissioned due to diminishing support from industry, and a new generation successor, e.g. Long-Term Evolution (LTE), is urgently required to replace the current network. The radio-based train control systems must be safety critical, which relies on a high-security Data Communication System (DCS). In this paper, a novel wireless network migration methodology in DCS is proposed. By using this methodology, the high-security required DCS performance in radio-based train control systems is maintained and the network migration cost, e.g. the used number of base station (BS), is reduced when updating the GSM-R to LTE.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 27 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Ting Cui, Feng Ding, Xiangli Li, Tasawar Hayat〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper focuses on the joint parameter and state estimation issue for observer canonical state-space systems with white noises in state equations and moving average noises in output equations. By means of the Kalman filtering and the gradient search, we derive a Kalman filtering based extended stochastic gradient algorithm. For purpose of achieving the higher parameter estimation accuracy, a Kalman filtering based multi-innovation extended stochastic gradient algorithm is proposed on the basis of the multi-innovation identification theory. Finally, the effectiveness of the proposed algorithms is validated through a numerical example.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 26 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of the Franklin Institute〈/p〉 〈p〉Author(s): Huan Xu, Lijuan Wan, Feng Ding, Ahmed Alsaedi, Tasawar Hayat〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper focuses on the recursive parameter estimation methods for the exponential autoregressive (ExpAR) model. Applying the negative gradient search and introducing a forgetting factor, a stochastic gradient and a forgetting factor stochastic gradient algorithms are presented. In order to improve the parameter estimation accuracy and the convergence rate, the multi-innovation identification theory is employed to derive a forgetting factor multi-innovation stochastic gradient algorithm. A simulation example is provided to test the effectiveness of the proposed algorithms.〈/p〉〈/div〉