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

Wenqi Xu, Xiaoping Liu*, Huanqing Wang, and Yucheng Zhou
International Journal of Control, Automation, and Systems, vol. 19, no. 1, pp.267-278, 2021

Abstract : 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 approximate the 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.

Keyword : Adaptive neural networks control, discrete-time control, nonlinear strcit-feedback systems, output feedback.

 
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