Ma Jiali, Xu Shengyuan, Ma Qian, Zhang Zhengqiang
IEEE Trans Neural Netw Learn Syst. 2020 Oct;31(10):4196-4205. doi: 10.1109/TNNLS.2019.2952709. Epub 2019 Dec 11.
In this article, the event-triggered-based adaptive neural network control problem is studied for a class of nonlinear time-delay systems with nonstrict-feedback structures and unknown control directions. First, a compensation system is introduced to handle the input delay and an observer is also designed to estimate the unmeasurable states. Then, by employing the neural networks and the variable separation approach, the adaptive backstepping method is applied to control the nonlinear systems with nonstrict-feedback structures. By codesigning the adaptive controller and the triggering mechanism, the input-to-state stability (ISS) assumption with respect to the measurement error is removed. Finally, it is shown that the proposed event-triggered adaptive controller can ensure the semiglobal boundedness of all the states in the closed-loop systems.
本文研究了一类具有非严格反馈结构且控制方向未知的非线性时滞系统基于事件触发的自适应神经网络控制问题。首先，引入一个补偿系统来处理输入延迟，并设计一个观测器来估计不可测量的状态。然后，通过使用神经网络和变量分离方法，将自适应反步方法应用于控制具有非严格反馈结构的非线性系统。通过协同设计自适应控制器和触发机制，消除了关于测量误差的输入到状态稳定性（ISS）假设。最后，结果表明所提出的事件触发自适应控制器能够确保闭环系统中所有状态的半全局有界性。
