Observer-based Adaptive Neural Network Output-feedback Control for Nonlinear Strict-feedback Discrete-time Systems
- Resource Type
- Article
- Authors
- Wenqi Xu; Xiaoping Liu; Huanqing Wang; Yucheng Zhou
- Source
- International Journal of Control, Automation, and Systems, 19(1), pp.267-278 Jan, 2021
- Subject
- 제어계측공학
- Language
- English
- ISSN
- 2005-4092
1598-6446
This paper focuses on an observer-based output-feedback controller design for a nonlinear discrete-timesystem. The major characteristics of this system is that all of the subsystems are in strict-feedback form and all thestates of the system are not measurable. An output tracking control problem is firstly considered in this paper. NNsare utilized to approximate unknown functions, while a state observer is designed to approximatethe unvailablestates. An adaptive controller is designed on the basis of the backstepping technique. On the basis of the Lyapunovanalysis approach, the boundedness of all the signals is provided. The feasibility of the proposed scheme is verifiedthrough a simulation example.