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<p>This paper proposes an event-triggered tracking control scheme for a class of strict-feedback nonlinear systems with high-order fully actuated (HOFA) subsystems. These systems, derived from physical laws, present challenges such as varying subsystem orders and unknown nonlinearities. Leveraging the HOFA framework, we design dynamic event-triggered controllers that significantly reduce control updates while maintaining stability. A threshold selection method is developed to adjust the dynamic event-triggered conditions. To ensure robustness against actuator failures, including partial loss of effectiveness and bias faults, we propose an adaptive fault-tolerant control scheme. In addition, the fuzzy logic systems (FLSs) approach is employed to approximate complete uncertain system functions, and the effects of the unknown weight vectors are eliminated by using adaptive estimation technology. Rigorous analysis proves that all closed-loop signals remain bounded, and system outputs asymptotically converge to reference trajectories despite uncertainties and faults. Simulations on an uncrewed aerial vehicle and an electromechanical system validate the method’s efficacy.</p>

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Dynamic Event-Triggered Fault-Tolerant Tracking Control for Fully Actuated Strict-Feedback Systems

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Jiaming Zhang,
  • Yang Liu,
  • Yulin Duan,
  • Wenling Li,
  • Bin Zhang

摘要

This paper proposes an event-triggered tracking control scheme for a class of strict-feedback nonlinear systems with high-order fully actuated (HOFA) subsystems. These systems, derived from physical laws, present challenges such as varying subsystem orders and unknown nonlinearities. Leveraging the HOFA framework, we design dynamic event-triggered controllers that significantly reduce control updates while maintaining stability. A threshold selection method is developed to adjust the dynamic event-triggered conditions. To ensure robustness against actuator failures, including partial loss of effectiveness and bias faults, we propose an adaptive fault-tolerant control scheme. In addition, the fuzzy logic systems (FLSs) approach is employed to approximate complete uncertain system functions, and the effects of the unknown weight vectors are eliminated by using adaptive estimation technology. Rigorous analysis proves that all closed-loop signals remain bounded, and system outputs asymptotically converge to reference trajectories despite uncertainties and faults. Simulations on an uncrewed aerial vehicle and an electromechanical system validate the method’s efficacy.