Finite-time adaptive neural command filtered control for pure-feedback time-varying constrained nonlinear systems with actuator faults

被引：9

作者：

Wu, Ziwen ^{[1
,2
,3
]}

Zhang, Tianping ^{[1
,2
]}

Xia, Xiaonan ^{[1
]}

Yi, Yang ^{[1
]}

机构：

[1] Yangzhou Univ, Coll Informat Engn, Dept Automat, Yangzhou 225127, Jiangsu, Peoples R China

[2] Yangzhou Univ, Coll Math Sci, Yangzhou 225002, Jiangsu, Peoples R China

[3] Anqing Normal Univ, Univ Key Lab Intelligent Percept & Comp Anhui Pro, Anqing 246133, Peoples R China

来源：

NEUROCOMPUTING | 2022年 / 490卷

基金：

中国国家自然科学基金;

关键词：

Finite-time adaptive control; Command filter; Actuator failures; Time-varying full state constraints; Unmodeled dynamics; DYNAMIC SURFACE CONTROL; FAILURE COMPENSATION; TRACKING CONTROL; OUTPUT; STABILIZATION;

D O I：

10.1016/j.neucom.2021.11.083

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, finite-time adaptive control (FTAC) is investigated for non-affine uncertain constrained nonlinear systems with actuator faults. The state constraints are dealt with by using nonlinear mapping (NM), and an auxiliary dynamical signal is used to handle the unknown dynamic uncertainties of the system. Based on the converted system, a FTAC strategy is designed via command filtered backstepping method. By introducing the compensation signals and adding them into the whole Lyapunov function, and with the help of the defined compact set in stability analysis, it is strictly proved that all signals are semi-globally practical finite-time stable (SGPFS) and all the states are within the specified open set. Simulation results verify the effectiveness of the proposed approach. (c) 2021 Elsevier B.V. All rights reserved.

引用

页码：193 / 205

页数：13

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