Neural Network Output-Feedback Consensus Fault-Tolerant Control for Nonlinear Multiagent Systems With Intermittent Actuator Faults

被引：50
|
作者：
Wu, Wei [1 ]
Li, Yongming [2 ]
Tong, Shaocheng [1 ]
机构：
[1] Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China
[2] Liaoning Univ Technol, Coll Sci, Jinzhou 121000, Peoples R China
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2023年 / 34卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Actuators; Artificial neural networks; Multi-agent systems; Fault tolerant systems; Fault tolerance; Nonlinear dynamical systems; Consensus control; Adaptive consensus control; intermittent actuator faults; NN state-observer; nonlinear multiagent systems (NMASs); LARGE-SCALE SYSTEMS; FAILURE COMPENSATION; TRACKING;
D O I：
10.1109/TNNLS.2021.3117364
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 article, the distributed adaptive neural network (NN) consensus fault-tolerant control (FTC) problem is studied for nonstrict-feedback nonlinear multiagent systems (NMASs) subjected to intermittent actuator faults. The NNs are applied to approximate nonlinear functions, and a NN state-observer is developed to estimate the unmeasured states. Then, to compensate for the influence of intermittent actuator faults, a novel distributed output-feedback adaptive FTC is then designed by co-designing the last virtual controller, and the problem of ``algebraic-loop'' can be solved. The stability of the closed-loop system is proven by using the Lyapunov theory. Finally, the effectiveness of the proposed FTC approach is validated by numerical and practical examples.
引用
收藏
页码：4728 / 4740
页数：13
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