Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

作     者：Chi Ma Dianbiao Dong Chi Ma;Dianbiao Dong

作者机构：the School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an 710072China 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2024年第11卷第4期

页      面：1039-1050页

核心收录：

学科分类：0711[理学-系统科学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：the National Natural Science Foundation of China(62203356) Fundamental Research Funds for the Central Universities of China(31020210502002) 

主　　题：Finite-time control multi-agent systems neural network prescribed performance control time-varying formation control 

摘      要：This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown *** eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the *** addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader *** address this problem,a neural network state observer based on the leader state information is ***,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite ***,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.