基于观测器的非严格反馈时滞非线性系统的神经网络自适应控制  

Observer⁃Based Adaptive Neural Network Control for Nonstrict⁃Feedback Nonlinear Systems With Time Delays

作　　者：刘祥 童东兵[1] 陈巧玉 LIU Xiang;TONG Dongbing;CHEN Qiaoyu(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,P.R.China;School of Mathematics,Physics and Statistics,Shanghai University of Engineering Science,Shanghai 201620,P.R.China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201620 [2]上海工程技术大学数理与统计学院,上海201620

出　　处：《应用数学和力学》2021年第6期586-594,共9页Applied Mathematics and Mechanics

基　　金：国家自然科学基金(61673257);中国博士后科学基金(2019M661322);上海市自然科学基金(20ZR1422400)。

摘　　要：针对一类非严格反馈的时滞非线性系统,研究了一类基于观测器的自适应神经网络控制问题.针对系统中存在未知状态变量的问题,设计了一个状态观测器.利用反步法和径向基神经网络的逼近特性,提出了一种自适应神经网络输出反馈控制方法.所设计的控制器保证了闭环系统中所有信号的半全局一致有界性.最后,通过仿真验证了所提控制方法的有效性.An observer⁃based adaptive neural network control problem was investigated for a class of nonstrict⁃feedback nonlinear systems with time delays.A state observer was constructed to estimate unknown variables in nonlinear systems.With the approximation ability of RBF NNs and the backstepping technique,an adaptive neural network output feedback control approach was proposed.The designed controller ensures the semi⁃glob⁃al uniform boundedness of all signals in the closed⁃loop system.Finally,the simulation example shows the ef⁃fectiveness of the proposed control approach.

关 键 词：神经网络 观测器 非严格反馈 自适应控制 

分 类 号：O175.13[理学—数学]