多智能体系统
非线性系统
计算机科学
事件(粒子物理)
控制理论(社会学)
人工智能
控制(管理)
物理
量子力学
作者
Yancheng Yan,Tieshan Li,Hongjing Liang
标识
DOI:10.1109/tcyb.2024.3524199
摘要
The prescribed-time output regulation problem is investigated for a class of uncertain nonlinear multiagent systems (MASs) subject to limited communication resources. To address this challenge, an event-based distributed neuro-adaptive prescribed-time control scheme comprising distributed prescribed-time observers, a dynamic event-triggered mechanism (DETM), and neuro-adaptive prescribed-time controllers is developed. Specifically, a distributed prescribed-time observer is constructed for each agent using event-based communications to estimate the states of the exosystem. The constructed observer operates without requiring prior knowledge of the exosystem dynamics or global information, ensuring that observation errors converge to a small neighborhood around zero within a user-determined time interval. Additionally, the incorporation of the DETM guarantees a positive lower bound on the interexecution intervals, thereby alleviating the communication demands. Building on this observer, neuro-adaptive prescribed-time controllers are derived for each agent, capable of maintaining the system states within a user-defined compact set without the need for prior knowledge of the initial system states. It is demonstrated that the regulated outputs converge to a region arbitrarily tuned by the user within a prescribed time, with all signals remaining bounded and Zeno behavior eliminated. Finally, two examples are exhibited to verify the effectiveness of the obtained results.
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