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Shaocheng Tong - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive fuzzy decentralized output feedback Control for nonlinear large scale Systems with unknown dead zone inputs
    IEEE Transactions on Fuzzy Systems, 2013
    Co-Authors: Shaocheng Tong
    Abstract:

    In this paper, the problem of Adaptive fuzzy decentralized backstepping Control is considered for a class of nonlinear large-scale strict-feedback Systems with unknown dead zones and immeasurable states. Fuzzy logic Systems are used to approximate the unknown nonlinear functions, and a state filter is designed to estimate the immeasurable states. Applying an Adaptive backstepping design technique and combining it with the dead-zone inverse method, an Adaptive fuzzy decentralized output-feedback backstepping Control is developed. It is proved that all the signals of the resulting closed-loop Adaptive Control System are semiglobally uniformly ultimately bounded, and tracking errors converge to a small neighborhood of the origin by appropriate choice of design parameters. Simulation results are given to demonstrate that the proposed Adaptive decentralized Control approach has a satisfactory Control performance.

  • Adaptive fuzzy backstepping output feedback Control for a class of mimo time delay nonlinear Systems based on high gain observer
    Nonlinear Dynamics, 2012
    Co-Authors: Yongming Li, Shaocheng Tong
    Abstract:

    In this paper, an Adaptive fuzzy backstepping output feedback Control approach is developed for a class of multiinput and multioutput (MIMO) nonlinear Systems with time delays and immeasurable states. Fuzzy logic Systems are employed to approximate the unknown nonlinear functions, and an Adaptive fuzzy high-gain observer is developed to estimate the unmeasured states. Using the designed high-gain observer, and combining the fuzzy Adaptive Control theory with the backstepping approach, an Adaptive fuzzy output feedback Control is constructed recursively. It is proved that all the signals of the closed-loop Adaptive Control System are semiglobally uniformly ultimately bounded (SUUB) and the tracking error converges to a small neighborhood of the origin.

  • observer based Adaptive fuzzy backstepping dynamic surface Control for a class of mimo nonlinear Systems
    Systems Man and Cybernetics, 2011
    Co-Authors: Shaocheng Tong, Yongming Li, Gang Feng, Tieshan Li
    Abstract:

    In this paper, an Adaptive fuzzy backstepping dynamic surface Control (DSC) approach is developed for a class of multiple-input-multiple-output nonlinear Systems with immeasurable states. Using fuzzy-logic Systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed to estimate the immeasurable states. By combining Adaptive-backstepping technique and DSC technique, an Adaptive fuzzy output-feedback backstepping-Control approach is developed. The proposed Control method not only overcomes the problem of “explosion of complexity” inherent in the backstepping-design methods but also overcomes the problem of unavailable state measurements. It is proved that all the signals of the closed-loop Adaptive-Control System are semiglobally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approach.

Yongming Li - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive fuzzy backstepping output feedback Control for a class of mimo time delay nonlinear Systems based on high gain observer
    Nonlinear Dynamics, 2012
    Co-Authors: Yongming Li, Shaocheng Tong
    Abstract:

    In this paper, an Adaptive fuzzy backstepping output feedback Control approach is developed for a class of multiinput and multioutput (MIMO) nonlinear Systems with time delays and immeasurable states. Fuzzy logic Systems are employed to approximate the unknown nonlinear functions, and an Adaptive fuzzy high-gain observer is developed to estimate the unmeasured states. Using the designed high-gain observer, and combining the fuzzy Adaptive Control theory with the backstepping approach, an Adaptive fuzzy output feedback Control is constructed recursively. It is proved that all the signals of the closed-loop Adaptive Control System are semiglobally uniformly ultimately bounded (SUUB) and the tracking error converges to a small neighborhood of the origin.

  • observer based Adaptive fuzzy backstepping dynamic surface Control for a class of mimo nonlinear Systems
    Systems Man and Cybernetics, 2011
    Co-Authors: Shaocheng Tong, Yongming Li, Gang Feng, Tieshan Li
    Abstract:

    In this paper, an Adaptive fuzzy backstepping dynamic surface Control (DSC) approach is developed for a class of multiple-input-multiple-output nonlinear Systems with immeasurable states. Using fuzzy-logic Systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed to estimate the immeasurable states. By combining Adaptive-backstepping technique and DSC technique, an Adaptive fuzzy output-feedback backstepping-Control approach is developed. The proposed Control method not only overcomes the problem of “explosion of complexity” inherent in the backstepping-design methods but also overcomes the problem of unavailable state measurements. It is proved that all the signals of the closed-loop Adaptive-Control System are semiglobally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approach.

S M Joshi - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive actuator failure compensation for nonlinear mimo Systems with an aircraft Control application
    Automatica, 2007
    Co-Authors: Xidong Tang, S M Joshi
    Abstract:

    A direct Adaptive approach is developed for Control of a class of multi-input multi-output (MIMO) nonlinear Systems in the presence of uncertain failures of redundant actuators. An Adaptive failure compensation Controller is designed which is capable of accommodating uncertainties in actuator failure time instants, values and patterns. A realistic situation is studied with fixed grouping of actuators and proportional actuation within actuator groups. The Adaptive Control System is analyzed, to show its desired stability and asymptotic tracking properties in the presence of actuator failure uncertainties. As an application, such an Adaptive Controller is used for actuator failure compensation of a twin otter aircraft longitudinal model, with design conditions verified and Control structure and Adaptive laws developed for a nonlinear aircraft dynamic model. The effectiveness of Adaptive failure compensation is demonstrated by simulation results.

  • Adaptive actuator failure compensation Control for mimo Systems
    International Journal of Control, 2004
    Co-Authors: Shuhao Chen, Gang Tao, S M Joshi
    Abstract:

    Two Adaptive failure compensation Control schemes based on MRAC are developed for a class of MIMO LTI Systems with unknown actuator failures. An effective Controller structure is proposed to achieve the desired plant-model output matching when implemented with matching parameters. Design conditions are specified for such nominal plant-model output matching. Two Adaptive versions of the nominal Controller are proposed and stable Adaptive laws are derived for updating the Controller parameters when plant parameters and failure parameters are unknown. All closed-loop signals are bounded and the plant outputs track the given reference outputs asymptotically, despite the uncertainties in actuator failures and plant parameters. Simulation results for an aircraft lateral dynamic model verify the desired Adaptive Control System performance in the presence of unknown rudder and aileron failures.

  • an Adaptive actuator failure compensation Controller for mimo Systems
    Conference on Decision and Control, 2002
    Co-Authors: Shuhao Chen, Gang Tao, S M Joshi
    Abstract:

    Two Adaptive Control schemes based on MRAC are developed for a class of MIMO Systems with unknown actuator failures. An effective Controller structure is proposed to achieve the desired plant-model output matching when implemented with matching parameters. Based on design conditions on the Controlled plant, which are needed for nominal plant-model output matching for a chosen Controller structure, two Adaptive versions of the nominal Controller are proposed and Adaptive laws are derived for updating the Controller parameters when plant and failure parameters are unknown. All closed-loop signals are bounded and the plant outputs track the given reference outputs asymptotically, despite the uncertainties in failures and plant parameters. Simulation results are presented to show the desired performance of the Adaptive Control System in the presence of unknown rudder and aileron failures in an aircraft lateral dynamic model.

Gang Tao - One of the best experts on this subject based on the ideXlab platform.

  • a multivariable Adaptive Controller for a quadrotor with guaranteed matching conditions
    Systems Science & Control Engineering, 2014
    Co-Authors: Justin M Selfridge, Gang Tao
    Abstract:

    This paper develops an Adaptive Control System for a quadrotor unmanned aerial vehicle. It employs a state feedback output tracking design for multi-input multi-output Systems, using a less restrictive matching condition than a state tracking design, and offers a simpler Controller structure than an output feedback design. Some key characteristics of the quadrotor dynamics are derived for Adaptive Control design which deals with System uncertainties from changing operating points. The plant–model matching is ensured despite of System parameter uncertainties which cannot be handled by an existing state tracking design. The Adaptive law is based on a parametrization using an LDS decomposition of the high-frequency gain matrix, which ensures closed-loop stability and asymptotic output tracking. A simulation study is carried out on the nonlinear quadrotor model, and results are presented to demonstrate the desired Adaptive System performance.

  • actuator failure compensation and attitude Control for rigid satellite by Adaptive Control using quaternion feedback
    Journal of The Franklin Institute-engineering and Applied Mathematics, 2014
    Co-Authors: Bin Jiang, Gang Tao, Yuehua Cheng
    Abstract:

    Abstract The attitude Control problem of a rigid satellite with actuator failure uncertainties and external disturbance is addressed using Adaptive Control method. A discontinuous Adaptive failure compensation Controller, using unit quaternion and angular velocities feedback, is designed to accommodate the external disturbance and actuator failures which are uncertain in time instants, values and patterns. A common approximate function is used to avoid System chattering caused by such discontinuous Control laws. The parameters of external disturbance and failure uncertainties are estimated directly by Adaptive laws, and the desired stability and output tracking properties of the Adaptive Control System are analyzed. Finally, simulation results of a rigid satellite with six reaction wheels are presented to illustrate the performance of the proposed Adaptive actuator failure compensation scheme.

  • Adaptive actuator failure compensation Control for mimo Systems
    International Journal of Control, 2004
    Co-Authors: Shuhao Chen, Gang Tao, S M Joshi
    Abstract:

    Two Adaptive failure compensation Control schemes based on MRAC are developed for a class of MIMO LTI Systems with unknown actuator failures. An effective Controller structure is proposed to achieve the desired plant-model output matching when implemented with matching parameters. Design conditions are specified for such nominal plant-model output matching. Two Adaptive versions of the nominal Controller are proposed and stable Adaptive laws are derived for updating the Controller parameters when plant parameters and failure parameters are unknown. All closed-loop signals are bounded and the plant outputs track the given reference outputs asymptotically, despite the uncertainties in actuator failures and plant parameters. Simulation results for an aircraft lateral dynamic model verify the desired Adaptive Control System performance in the presence of unknown rudder and aileron failures.

  • an Adaptive actuator failure compensation Controller for mimo Systems
    Conference on Decision and Control, 2002
    Co-Authors: Shuhao Chen, Gang Tao, S M Joshi
    Abstract:

    Two Adaptive Control schemes based on MRAC are developed for a class of MIMO Systems with unknown actuator failures. An effective Controller structure is proposed to achieve the desired plant-model output matching when implemented with matching parameters. Based on design conditions on the Controlled plant, which are needed for nominal plant-model output matching for a chosen Controller structure, two Adaptive versions of the nominal Controller are proposed and Adaptive laws are derived for updating the Controller parameters when plant and failure parameters are unknown. All closed-loop signals are bounded and the plant outputs track the given reference outputs asymptotically, despite the uncertainties in failures and plant parameters. Simulation results are presented to show the desired performance of the Adaptive Control System in the presence of unknown rudder and aileron failures in an aircraft lateral dynamic model.

Inalhan Gokhan - One of the best experts on this subject based on the ideXlab platform.

  • Reinforcement learning based closed‐loop reference model Adaptive flight Control System design
    'Wiley', 2021
    Co-Authors: Yuksek Burak, Inalhan Gokhan
    Abstract:

    In this study, we present a reinforcement learning (RL)‐based flight Control System design method to improve the transient response performance of a closed‐loop reference model (CRM) Adaptive Control System. The methodology, known as RL‐CRM, relies on the generation of a dynamic adaption strategy by implementing RL on the variable factor in the feedback path gain matrix of the reference model. An actor‐critic RL agent is designed using the performance‐driven reward functions and tracking error observations from the environment. In the training phase, a deep deterministic policy gradient algorithm is utilized to learn the time‐varying adaptation strategy of the design parameter in the reference model feedback gain matrix. The proposed Control structure provides the possibility to learn numerous adaptation strategies across a wide range of flight and vehicle conditions instead of being driven by high‐fidelity simulators or flight testing and real flight operations. The performance of the proposed System was evaluated on an identified and verified mathematical model of an agile quadrotor platform. Monte‐Carlo simulations and worst case analysis were also performed over a benchmark helicopter example model. In comparison to the classical model reference Adaptive Control and CRM‐Adaptive Control System designs, the proposed RL‐CRM Adaptive flight Control System design improves the transient response performance on all associated metrics and provides the capability to operate over a wide range of parametric uncertainties

  • Reinforcement learning based closed-loop reference model Adaptive flight Control System design
    'Wiley', 2020
    Co-Authors: Yuksek Burak, Inalhan Gokhan
    Abstract:

    In this study, we present a reinforcement learning (RL)-based flight Control System design method to improve the transient response performance of a closed-loop reference model (CRM) Adaptive Control System. The methodology, known as RL-CRM, relies on the generation of a dynamic adaption strategy by implementing RL on the variable factor in the feedback path gain matrix of the reference model. An actor-critic RL agent is designed using the performance-driven reward functions and tracking error observations from the environment. In the training phase, a deep deterministic policy gradient algorithm is utilized to learn the time-varying adaptation strategy of the design parameter in the reference model feedback gain matrix. The proposed Control structure provides the possibility to learn numerous adaptation strategies across a wide range of flight and vehicle conditions instead of being driven by high-fidelity simulators or flight testing and real flight operations. The performance of the proposed System was evaluated on an identified and verified mathematical model of an agile quadrotor platform. Monte-Carlo simulations and worst case analysis were also performed over a benchmark helicopter example model. In comparison to the classical model reference Adaptive Control and CRM-Adaptive Control System designs, the proposed RL-CRM Adaptive flight Control System design improves the transient response performance on all associated metrics and provides the capability to operate over a wide range of parametric uncertainties