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  • 1
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    A Fundamental Wave Amplitude Prediction Algorithm Based on Fuzzy Neural Network for Harmonic Elimination of Electric Arc Furnace Current (2015)
    Hindawi
    Details
    Publication Date: 2015-10-05
    Description: Electric arc furnace (EAF) causes the harmonics to impact on the supply network greatly and harmonic elimination is a very important research work for the power quality associated with EAF. In the paper, a fundamental wave amplitude prediction algorithm based on fuzzy neural network for harmonic elimination of EAF current is proposed. The proposed algorithm uses the learning ability of the neural network to refine Takagi-Sugeno type fuzzy rules and the inputs are the average of the current measured value in different time intervals. To verify the effectiveness of the proposed algorithm, some experiments are performed to compare the proposed algorithm with the back-propagation neural networks, and the field data collected at an EAF are used in the experiments. Moreover, the measured amplitudes of fundamental waves of field data are obtained by the sliding-window-based discrete Fourier transform on the field data. The experiments results show that the proposed algorithm has higher precision. The real curves also verify that the amplitude of fundamental wave current could be predicted accurately and the harmonic elimination of EAF would be realized based on the proposed algorithm.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 2
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    An Improved Directional Broadcast Algorithm Based on Brownian Motion (2014)
    Hindawi
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    Publication Date: 2014-07-25
    Description: Several broadcast algorithms have been developed in recent years. However, the problem of reducing routing overhead in ad hoc networks is always to be concerned. This paper proposes an improved directional broadcast algorithm based on Brownian motion for AODV protocol (DBB-AODV). We bring Brownian motion into network model and gain the distribution of the nodes which encountered destination before. This algorithm uses encounter records to predict the direction to destination and forwards RREQ packets with reasonable probability according to the distribution just mentioned. Simulation results indicate that DBB-AODV saves up to 20% of average routing overhead compared to the probabilistic protocol and about 80% of the blind flooding.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Hindawi
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  • 3
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    Robust Observer Based Disturbance Rejection Control for Euler-Lagrange Systems (2016)
    Hindawi
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    Publication Date: 2016-01-01
    Description: Robust disturbance rejection control methodology is proposed for Euler-Lagrange systems, and parameters optimization strategy for the observer is explored. First, the observer based disturbance rejection methodology is analyzed, based on which the disturbance rejection paradigm is proposed. Thus, a disturbance observer (DOB) with partial feedback linearization and a low-pass filter is proposed for nonlinear dynamic model under relaxed restrictions of the generalized disturbance. Then, the outer-loop backstepping controller is designed for desired tracking performance. Considering that the parameters of DOB cannot be obtained directly based on Lyapunov stability analysis, parameter of DOB is optimized under standardH∞control framework. By analyzing the influence of outer-loop controller on the inner-loop observer parameter, robust stability constraint is proposed to guarantee the robust stability of the closed-loop system. Experiment on attitude tracking of an aircraft is carried out to show the effectiveness of the proposed control strategy.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 4
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    A Fundamental Wave Amplitude Prediction Algorithm Based on Fuzzy Neural Network for Harmonic Elimination of Electric Arc Furnace Current (2015)
    Hindawi
    Details
    Publication Date: 2015-01-01
    Description: Electric arc furnace (EAF) causes the harmonics to impact on the supply network greatly and harmonic elimination is a very important research work for the power quality associated with EAF. In the paper, a fundamental wave amplitude prediction algorithm based on fuzzy neural network for harmonic elimination of EAF current is proposed. The proposed algorithm uses the learning ability of the neural network to refine Takagi-Sugeno type fuzzy rules and the inputs are the average of the current measured value in different time intervals. To verify the effectiveness of the proposed algorithm, some experiments are performed to compare the proposed algorithm with the back-propagation neural networks, and the field data collected at an EAF are used in the experiments. Moreover, the measured amplitudes of fundamental waves of field data are obtained by the sliding-window-based discrete Fourier transform on the field data. The experiments results show that the proposed algorithm has higher precision. The real curves also verify that the amplitude of fundamental wave current could be predicted accurately and the harmonic elimination of EAF would be realized based on the proposed algorithm.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 5
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    Sediment Deposition Risk Analysis and PLSR Model Research for Cascade Reservoirs Upstream of the Yellow River (2015)
    Hindawi
    Details
    Publication Date: 2015-01-01
    Description: It is difficult to effectively identify and eliminate the multiple correlation influence among the independent factors by least-squares regression. Focusing on this insufficiency, the sediment deposition risk of cascade reservoirs and fitting model of sediment flux into the reservoir are studied. The partial least-squares regression (PLSR) method is adopted for modeling analysis; the model fitting is organically combined with the non-model-style data content analysis, so as to realize the regression model, data structure simplification, and multiple correlations analysis among factors; meanwhile the accuracy of the model is ensured through cross validity check. The modeling analysis of sediment flux into the cascade reservoirs of Long-Liu section upstream of the Yellow River indicates that partial least-squares regression can effectively overcome the multiple correlation influence among factors, and the isolated factor variables have better ability to explain the physical cause of measured results.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 6
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    Bi-Objective Optimization Method and Application of Mechanism Design Based on Pigs' Payoff Game Behavior (2012)
    Hindawi
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    Publication Date: 2012-01-01
    Description: It takes two design goals as different game players and design variables are divided into strategy spaces owned by corresponding game player by calculating the impact factor and fuzzy clustering. By the analysis of behavior characteristics of two kinds of intelligent pigs, the big pig's behavior is cooperative and collective, but the small pig's behavior is noncooperative, which are endowed with corresponding game player. Two game players establish the mapping relationship between game players payoff functions and objective functions. In their own strategy space, each game player takes their payoff function as monoobjective for optimization. It gives the best strategy upon other players. All the best strategies are combined to be a game strategy set. With convergence and multiround game, the final game solution is obtained. Taking bi-objective optimization of luffing mechanism of compensative shave block, for example, the results show that the method can effectively solve bi-objective optimization problems with preferred target and the efficiency and accuracy are also well.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 7
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    Improved NN-GM(1,1) for Postgraduates’ Employment Confidence Index Forecasting (2014)
    Hindawi
    Details
    Publication Date: 2014-01-01
    Description: Postgraduates’ employment confidence index (ECI) forecasting can help the university to predict the future trend of postgraduates’ employment. However, the common forecast method based on the grey model (GM) has unsatisfactory performance to a certain extent. In order to forecast postgraduates’ ECI efficiently, this paper discusses a novel hybrid forecast model using limited raw samples. Different from previous work, the residual modified GM(1,1) model is combined with the improved neural network (NN) in this work. In particullar, the hybrid model reduces the residue of the standard GM(1,1) model as well as accelerating the convergence rate of the standard NN. After numerical studies, the illustrative results are provided to demonstrate the forecast performance of the proposed model. In addition, some strategies for improving the postgraduates’ employment confidence have been discussed.
    Print ISSN: 1024-123X
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    Topics: Mathematics , Technology
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  • 8
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    Damage Detection of Bridge Structure Based on SVM (2013)
    Hindawi
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    Publication Date: 2013-01-01
    Description: For bridge management and maintenance, it is important to detect the damage of bridge pier. Due to the complexity of damage detection, an effective method is very interesting. Support vector machine (SVM) is used to detect the damage of bridge pier in this paper. To improve the detection accuracy of SVM, Grubbs’ test method is adopted to delete the outliers for SVM. Then, a numerical analysis is used to determine the input parameters for SVM. Lastly, the comparison results between the proposed SVM and the actual measure value suggested that the proposed SVM is a powerful tool for detecting damage of bridge pier.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 9
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    Multiobjective Optimization Method for Multichannel Microwave Components of Active Phased Array Antenna (2016)
    Hindawi
    Details
    Publication Date: 2016-01-01
    Description: Multichannel microwave components are widely used and the active phased array antenna is a typical representative. The high power generated from T/R modules in active phased array antenna (APAA) leads to the degradation of its electrical performances, which seriously restricts the development of high-performance APAA. Therefore, to meet the demand of thermal design for APAA, a multiobjective optimization design model of cold plate is proposed. Furthermore, in order to achieve temperature uniformity and case temperature restrictions of APAA simultaneously, optimization model of channel structure is developed. Besides, an airborne active phased array antenna was tested as an example to verify the validity of the optimization model. The valuable results provide important reference for engineers to enhance thermal design technology of antennas.
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  • 10
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    Balancing Long Lifetime and Satisfying Fairness in WBAN Using a Constrained Markov Decision Process (2015)
    Hindawi
    Details
    Publication Date: 2015-01-01
    Description: As an important part of the Internet of Things (IOT) and the special case of device-to-device (D2D) communication, wireless body area network (WBAN) gradually becomes the focus of attention. Since WBAN is a body-centered network, the energy of sensor nodes is strictly restrained since they are supplied by battery with limited power. In each data collection, only one sensor node is scheduled to transmit its measurements directly to the access point (AP) through the fading channel. We formulate the problem of dynamically choosing which sensor should communicate with the AP to maximize network lifetime under the constraint of fairness as a constrained markov decision process (CMDP). The optimal lifetime and optimal policy are obtained by Bellman equation in dynamic programming. The proposed algorithm defines the limiting performance in WBAN lifetime under different degrees of fairness constraints. Due to the defect of large implementation overhead in acquiring global channel state information (CSI), we put forward a distributed scheduling algorithm that adopts local CSI, which saves the network overhead and simplifies the algorithm. It was demonstrated via simulation that this scheduling algorithm can allocate time slot reasonably under different channel conditions to balance the performances of network lifetime and fairness.
    Print ISSN: 1687-5869
    Electronic ISSN: 1687-5877
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Hindawi
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