| 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 |
| |
| 引用本文： | 刘祥,童东兵,陈巧玉.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[J].应用数学和力学,2021,42(6):586-594. |
| |
| 作者姓名： | 刘祥 童东兵 陈巧玉 |
| |
| 作者单位： | 1.上海工程技术大学 电子电气工程学院，上海 201620; |
| |
| 基金项目： | 上海市自然科学基金（20ZR1422400）国家自然科学基金(61673257)；中国博士后科学基金(2019M661322) |
| |
| 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.
|
| 关 键 词： | 神经网络 观测器 非严格反馈 自适应控制 |
| 收稿时间： | 2020-10-23 |
Observer-Based Adaptive Neural Network Control for Nonstrict-Feedback Nonlinear Systems With Time Delays |
| |
| Institution: | 1. School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, P.R.China;2. School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, P.R.China |
| |
| Abstract: | 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-global uniform boundedness of all signals in the closed-loop system. Finally, the simulation example shows the effectiveness of the proposed control approach. |
| |
| Keywords: | |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《应用数学和力学》浏览原始摘要信息 |
| 点击此处可从《应用数学和力学》下载免费的PDF全文 |
