控制理论(社会学)
李雅普诺夫函数
控制器(灌溉)
二部图
计算机科学
有界函数
多智能体系统
非线性系统
Lyapunov稳定性
功能(生物学)
拓扑(电路)
数学
控制(管理)
人工智能
理论计算机科学
图形
物理
量子力学
进化生物学
生物
数学分析
组合数学
农学
作者
Shanlin Liu,Ben Niu,Hamid Reza Karimi,Xudong Zhao
标识
DOI:10.1016/j.chaos.2023.114367
摘要
This article presents a self-triggered bipartite fault-tolerant consensus control scheme in a fixed-time stability sense for multiagent systems (MASs) with function constraints on states. Neural networks are introduced to identify unknown nonlinearities, thereby relaxing constraints on unknown functions. Then, based on time-varying barrier Lyapunov functions including time and previous states, all states of the considered MASs are constrained to given ranges. In addition, to improve the utilization of system transmission resources, a self-triggered control method in which the next triggering time can be computed according to the current information of the controller is proposed. By applying the Lyapunov theory, the designed self-triggered controller can ensure that all signals containing consensus tracking errors are fixed-time bounded under a given communication topology, and the Zeno phenomenon is successfully avoided. Finally, a practical example is provided to testify the feasibility of the developed control scheme.
科研通智能强力驱动
Strongly Powered by AbleSci AI