Adaptive backstepping control for strict‐feedback non‐linear systems with input delay and disturbances. Issue 4 (18th February 2019)

• Record Type: Journal Article
• Authors: Ma, Jiali; Xu, Shengyuan; Cui, Guozeng; Chen, Weimin; Zhang, Zhengqiang
• Is Part Of: IET control theory & applications. Volume 13:Issue 4(2019)
• Page Start: 506
• Page End: 516
• Publication Date: 2019-02-18
• Subjects: nonlinear control systems -- uncertain systems -- control nonlinearities -- feedback -- Lyapunov methods -- approximation theory -- control system synthesis -- adaptive control -- closed loop systems -- neurocontrollers -- stability -- delays; adaptive backstepping control -- strict‐feedback nonlinear systems -- input delay -- adaptive neural networks control -- Pade approximation method -- auxiliary system -- nonlinear functions -- backstepping technique -- adaptive NNs controllers -- closed‐loop systems -- Lyapunov stability theorem -- uncertain nonlinear systems; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2018.5326
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : The problem of adaptive neural networks (NNs) control for a class of uncertain non‐linear systems with input delay and disturbances is studied. By using Pade approximation method, an auxiliary system is constructed to compensate the input delay based on the introduced variable. NNs are used to approximate the unknown non‐linear functions. With the aid of backstepping technique, adaptive NNs controllers are designed which can guarantee all the signals in the closed‐loop systems are semi‐globally uniformly ultimately bounded and the tracking error can be adjusted around the origin with a small neighbourhood. The stability of the closed‐loop systems is proved by using the Lyapunov stability theorem and two simulation examples are given to illustrate the effectiveness of the proposed methods.