This paper presents a novel event-triggered adaptive fuzzy fault-tolerant control approach for a class of uncertain nonlinear systems without the requirement for the online fault estimation. The main objective is to guarantee the stability of the faulty systems consuming less communication resources. Different from the existing results, a specific event-trigger error is designed, which is expected to reduce the amount of communications further. The generalized fuzzy hyperbolic model is employed to approximate the ideal fault-tolerant control policy in the framework of event-based sampled-data control. Based on the stability theory for nonlinear impulsive dynamical systems, the fuzzy adaptive control policy with a novel event-based weight update law is proposed to guarantee the stability of the closed-loop faulty system. In addition, the existence of a positive lower bound of the interevent interval is ensured to avoid the Zeno phenomenon. Finally, the simulation results are provided to show the effectiveness and better performance of the proposed scheme.

中文翻译：

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一类非线性系统的基于事件的模糊自适应容错控制


本文针对一类不确定非线性系统提出了一种新颖的事件触发自适应模糊容错控制方法，无需在线故障估计。主要目标是消耗较少的通信资源来保证故障系统的稳定性。与现有结果不同，设计了特定的事件触发错误，有望进一步减少通信量。在基于事件的采样数据控制框架中，采用广义模糊双曲线模型来逼近理想的容错控制策略。基于非线性脉冲动力系统的稳定性理论，提出了基于事件的权重更新律的模糊自适应控制策略，以保证闭环故障系统的稳定性。此外，确保事件间隔的正下界的存在以避免芝诺现象。最后，提供了仿真结果，表明了所提出方案的有效性和更好的性能。