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  • 1
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    Input and Output Performance of M-MRAC in the Presence of Bounded Disturbances (2011)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This paper presents performance analysis of novel modified model reference adaptive control (M-MRAC) architecture in conjunction with different robust adaptive laws for the uncertain linear systems subject to unknown but bounded disturbances. It is shown that for any robust adaptive law the tracking error of the M-MRAC system can be arbitrarily decreased in transient and in the steady-state by increasing the adaptation rate, without generating high frequency oscillations in the control signal, which are unavoidable in conventional MRAC systems for large adaptation rates. Moreover, the generated adaptive control signal arbitrary closely tracks the ideal control signal when the error feedback gain is simultaneously increased with the adaptation rate, according to derived rule. The results are demonstrated via simulations.
    Keywords: Mathematical and Computer Sciences (General)
    Type: ARC-E-DAA-TN1961 , AIAA Guidance, Navigation and Control Conference; Aug 02, 2010 - Aug 05, 2010; TOronto, Ontario; Canada
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  • 2
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    Predicting Loss-of-Control Boundaries Toward a Piloting Aid (2012)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.
    Keywords: Avionics and Aircraft Instrumentation
    Type: ARC-E-DAA-TN5393 , AIAA Infotech@Aerospace 2012; Jun 19, 2012 - Jun 21, 2012; Garden Grove, CA; United States
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  • 3
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    M-MRAC for Nonlinear Systems with Bounded Disturbances (2011)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This paper presents design and performance analysis of a modified reference model MRAC (M-MRAC) architecture for a class of multi-input multi-output uncertain nonlinear systems in the presence of bounded disturbances. M-MRAC incorporates an error feedback in the reference model definition, which allows for fast adaptation without generating high frequency oscillations in the control signal, which closely follows the certainty equivalent control signal. The benefits of the method are demonstrated via a simulation example of an aircraft's wing rock motion.
    Keywords: Aircraft Stability and Control
    Type: ARC-E-DAA-TN4164 , 50th IEEE Conference on Decision and Control; Dec 12, 2012; Orlando, FL; United States
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  • 4
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    On the Robustness Properties of M-MRAC (2012)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The paper presents performance and robustness analysis of the modified reference model MRAC (model reference adaptive control) or M-MRAC in short, which differs from the conventional MRAC systems by feeding back the tracking error to the reference model. The tracking error feedback gain in concert with the adaptation rate provides an additional capability to regulate not only the transient performance of the tracking error, but also the transient performance of the control signal. This differs from the conventional MRAC systems, in which we have only the adaptation rate as a tool to regulate just the transient performance of the tracking error. It is shown that the selection of the feedback gain and the adaptation rate resolves the tradeoff between the robustness and performance in the sense that the increase in the feedback gain improves the behavior of the adaptive control signal, hence improves the systems robustness to time delays (or unmodeled dynamics), while increasing the adaptation rate improves the tracking performance or systems robustness to parametric uncertainties and external disturbances.
    Keywords: Aircraft Stability and Control
    Type: ARC-E-DAA-TN5305 , AIAA Infotech@Aerospace; Jun 19, 2012 - Jun 21, 2012; Garden Grove, CA; United States
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  • 5
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    Adaptive Control with Reference Model Modification (2012)
    In:  CASI
    Details
    Publication Date: 2019-07-12
    Description: This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example
    Keywords: Aircraft Stability and Control
    Type: ARC-E-DAA-TN4734
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  • 6
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    Coordinated Turn Trajectory Generation and Tracking Control for Multi-rotors Operating in Urban Environment (2019)
    In:  CASI
    Details
    Publication Date: 2019-07-20
    Description: The paper presents an efficient trajectory generation and tracking approach for multi-rotor air vehicles operating in urban environment, which takes into account uncertainties in the urban wind field and in the vehicle's parameters. Generated trajectories are sufficiently smooth, based on the differential flatness of the vehicle's dynamics and optimal in the sense of minimum agility and time. They pass through given set of way points, guarantee flight without a side-slip, and satisfy vehicle's dynamics and actuator constraints. In addition, an algorithm is presented to compute the required power to traverse the generated trajectory. Presented algorithms are implementable in real time using on-board computers. They do not take into account the vehicle's existing flight controller, hence there is no guarantee that the controller will be able to provide acceptable tracking of the generated trajectory, especially in the presence of atmospheric disturbances. To this end, we propose an adaptive augmentation algorithm to improve vehicle's performance by taking into account the effects of disturbances and on-line estimates of vehicle's existing flight controller's gains. The algorithms have been verified by simulations using DJI S1000 octocopter's model.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN64488 , AIAA Science and Technology Forum and Exposition; Jan 07, 2019 - Jan 11, 2019; San Diego, CA; United States
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  • 7
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    M-MRAC With Normalization (2014)
    In:  CASI
    Details
    Publication Date: 2019-07-20
    Description: This paper presents a normalization based modified reference model adaptive control method for multi-input multi-output (MIMO) uncertain systems in the presence of bounded external disturbances. It has been shown that desired tracking performance can be achieved for the system's output and input signals with the proper choice of design parameters. The resulting adaptive control signal satisfies a second order linear time invariant (LTI) system, which is the effect of the normalization term in the adaptive laws. This LTI system provides the guideline for the design parameter selection. The theoretical findings are confirmed via a simulation example.
    Keywords: Aircraft Stability and Control
    Type: ARC-E-DAA-TN17809 , IEEE Conference on Decision and Control (CDC); Dec 15, 2014 - Dec 17, 2014; Los Angeles, CA; United States
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  • 8
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    Input Constrained M-MRAC for Multirotors Operating in an Urban Environment (2019)
    In:  CASI
    Details
    Publication Date: 2019-07-20
    Description: The paper presents a modified model reference adaptive control (M-MRAC) for multi-input multi-output nonlinear dynamical systems with time varying parametric uncertainties and bounded external disturbances. It uses a prediction model to rapidly generate adaptive estimates of the system's uncertainties with adjustable errors that converge to a small neighborhood of the origin. A sufficient condition is derived to specify the region of attraction in the space of initialization errors, design parameters and external commends. The approach is applied to thrust controlled multi-rotor air vehicles operating in an urban environment. It is shown that the designed controller can provide a good tracking of a given trajectory in the unknown urban wind field, assuming that the maximum thrust generated by the rotors is known. The performance of the algorithms are demonstrated in simulations.
    Keywords: Aircraft Stability and Control; Systems Analysis and Operations Research
    Type: ARC-E-DAA-TN64491 , ARC-E-DAA-TN63561 , AIAA Science and Technology Forum and Exposition; Jan 07, 2019 - Jan 11, 2019; San Diego, CA; United States
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  • 9
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    Stall Recovery Guidance Using Fast Model Predictive Control (2017)
    In:  CASI
    Details
    Publication Date: 2019-07-20
    Description: Based on a detailed analysis of recent loss-of-control events, the Aircraft State Awareness Joint Safety Analysis Team has identified the need to develop algorithms and display strategies to provide control guidance for recovery from approach-to-stall or stall. In order to be effective, such guidance should enhance the pilots ability to execute the Federal Aviation Administrations recommended stall recovery procedure. This paper explores the use of a fast model predictive control algorithm that determines near optimal recovery guidance, which quantifies the aircraft configuration and situation dependent recovery information required to maximize the effectiveness of the recovery. This information includes the magnitude of the initial pitch down maneuver, the specific amount of airspeed and thrust needed before pulling out of the recovery dive, as well as the maximum pitch-up rate that can be sustained without causing a secondary stall. The algorithm was integrated and tested with an in-house desktop simulator that implements the General Transport Aircraft model and the associated stall aircraft dynamics. Preliminary results are presented to demonstrate the use of the proposed approach as a recovery aid for pilots.
    Keywords: Physics (General); Air Transportation and Safety; Mathematical and Computer Sciences (General)
    Type: ARC-E-DAA-TN37986 , AIAA Guidance, Navigation, and Control Conference; Jan 09, 2017 - Jan 13, 2017; Grapevine, TX; United States
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  • 10
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    Real-Time Path Planning for Multi-copters flying in UTM -TCL4 (2019)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: NASA's UAS Traffic management (UTM) -TCL-4 focuses on safely enabling large scale small UAS oper- ations in low altitude airspace in dense urban regions. This paper presents an operational architecture of an autonomous unmanned aerial vehicle operating in TCL4. An on-line path planning scheme is proposed which can effectively plan for feasible paths in real time with TCL-4 constraints. An end to end system is designed and tested in high fidelity Reflection architecture which demonstrates the feasibility of the approach.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN63605 , AIAA SciTech Forum; Jan 07, 2019 - Jan 11, 2019; San Diego, CA; United States
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