Observer-based Adaptive Neural Network Output-feedback Control for Nonlinear Strict-feedback Discrete-time Systems

被引：0
作者：
Wenqi Xu
Xiaoping Liu
Huanqing Wang
Yucheng Zhou
机构：
[1] Shandong Jianzhu University,School of Information and Electrical Engineering
[2] Lakehead University,Faculty of Engineering
来源：
International Journal of Control, Automation and Systems | 2021年 / 19卷
关键词：
Adaptive neural networks control; discrete-time control; nonlinear strcit-feedback systems; output feedback;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper focuses on an observer-based output-feedback controller design for a nonlinear discrete-time system. The major characteristics of this system is that all of the subsystems are in strict-feedback form and all the states of the system are not measurable. An output tracking control problem is firstly considered in this paper. NNs are utilized to approximate unknown functions, while a state observer is designed to approximatethe unvailable states. An adaptive controller is designed on the basis of the backstepping technique. On the basis of the Lyapunov analysis approach, the boundedness of all the signals is provided. The feasibility of the proposed scheme is verified through a simulation example.
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页码：267 / 278
页数：11
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