Adaptive Neural Network Finite-Time Prescribed Performance Consensus Control for a Class of Second-Order Multi-Agent Systems
作者机构：School of Mechanical Engineering Northwestern Polytechnical University Xi'an 710072P.R.China
出 版 物：《Guidance, Navigation and Control》 (制导、导航与控制（英文）)
年 卷 期：2024年第4卷第2期
页 面：80-103页
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题：Neural network prescribed performance multi-agent systems finite time
摘 要：This research investigates the semi-global practicalfinite-time prescribed performance consensus control issue for a class of second-order multi-agent systems with unknown nonlinear *** the previousfinite-time control set by afinite-time performance function,we givefinite-time control by constraining the terminal sliding manifold in a performance *** addition,an adaptive neural network control scheme is designed,which simplifies the controller and avoids the chattering issue existing in traditional sliding mode ***,a novel adaptivefinite-time prescribed performance consensus control strategy is designed,which ensures that all system variables are semi-globally practicalfinite-time stable and consensus errors of the multi-agent systems converge within the prescribed region infinite *** effectiveness and practicality of the presented control strategy are evaluated by conducting simulation cases.
维普期刊数据库