文献类型：期刊文献

英文题名：Fixed-time self-structuring neural network cooperative tracking control of multi-robot systems with actuator faults

作者：Liu, Haitao[1,2];Huang, Xin[1];Tian, Xuehong[1,2];Yuan, Jianbin[1]

机构：[1]Guangdong Ocean Univ, Sch Mech & Power Engn, Zhanjiang 524088, Peoples R China;[2]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen, Peoples R China

年份：2022

卷号：32

期号：16

起止页码：9053

外文期刊名：INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL

收录：SCI-EXPANDED(收录号：WOS:000829191800001)、、EI(收录号：20223012402485)、Scopus(收录号：2-s2.0-85134613132)、WOS

基金：Science and Technology Planning Project of Zhanjiang City, Grant/Award Numbers: 2021E05012, 2020B01267; Department of Education of Guangdong Province, Grant/Award Number: 2021ZDZX1041; 2019 "Chong First-class" Provincial Financial Special Funds Construction Project, Grant/Award Number: 231419019

语种：英文

外文关键词：actuator faults; fixed-time cooperative control; fixed-time state observer; multi-robot systems; self-structuring neural networks

外文摘要：In this study, a fixed-time adaptive cooperative controller by a self-structuring neural network is proposed, and actuator faults are considered for multi-robot systems. First, a novel fixed-time leader state observer is developed to estimate the state information of the leader and pass on to other followers without measuring the leader's velocity. Second, a fixed-time cooperative controller is designed to achieve fast response and high precision. Third, a fixed-time convergent self-structuring neural network is designed to improve the approximation accuracy affected by system uncertainties and actuator faults. A new neuronal splitting strategy is designed to avoid excessive computational burden caused by too many neurons. Next, the Lyapunov stability theorem is employed to demonstrate that the whole error closed-loop system can globally converge to a small region around zero in a fixed time. Finally, a simulation example on multi-robot systems shows that the proposed fixed-time adaptive cooperative controller is able to obtain satisfactory performances in the presence of uncertainties from external disturbances, actuator faults and other causes.