This article presents the observer-based event-triggered adaptive hybrid fuzzy dynamic surface control strategy for a category of uncertain nonstrict-feedback fractional-order nonlinear multi-input multi-output systems, including unknown time-varying delays and actuator faults. First, an adaptive hybrid fuzzy state observer and a serial-parallel estimation system are constructed to estimate the unmeasured system states and incorporate them into the control design scheme, respectively, where some appropriate fuzzy logic systems are introduced to approximate the unknown nonlinear functions. According to the dynamic surface control technique, the designed adaptive fuzzy control approach can surmount the deficiency of “complexity explosion.” Then, an observer-based adaptive event-triggered control algorithm is developed by constructing the Lyapunov–Krasovskii functionals and estimating the compounded disturbances. Furthermore, it is proved that under the drive of the reference signals, all the signals in the closed-loop system are semiglobally uniformly ultimately bounded and Zeno behavior can be successfully excluded. Finally, an example with numerical simulations is utilized to exhibit the applicability of the obtained observer-based event-triggered adaptive fuzzy control approach.

中文翻译：

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基于观测器的事件触发自适应模糊控制分数阶时变延迟 MIMO 系统对抗执行器故障


本文针对一类不确定的非严格反馈分数阶非线性多输入多输出系统（包括未知时变延迟和执行器故障）提出了基于观测器的事件触发自适应混合模糊动态表面控制策略。首先，构建自适应混合模糊状态观测器和串并联估计系统来分别估计未测量的系统状态并将其纳入控制设计方案，其中引入一些适当的模糊逻辑系统来逼近未知的非线性函数。根据动态表面控制技术，设计的自适应模糊控制方法可以克服“复杂性爆炸”的缺陷。然后，通过构造 Lyapunov-Krasovskii 泛函并估计复合扰动，开发了一种基于观测器的自适应事件触发控制算法。进一步证明，在参考信号的驱动下，闭环系统中的所有信号都是半全局一致最终有界的，并且可以成功排除Zeno行为。最后，利用数值模拟的例子来展示所获得的基于观测器的事件触发自适应模糊控制方法的适用性。