Consensus of Nonlinear Uncertain Delayed Multiagent Systems Modeled by PDEs via Adaptive Boundary Control

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2025-04-09 DOI:10.1109/TCYB.2025.3554844
Xu Zhang;Biao Luo;Zi-Peng Wang;Xiaodong Xu;Chunhua Yang
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Abstract

Under the influence of nonlinearity, time-varying delay, and uncertainty, the consensus problem is concerned in this study for multiagent systems modeled by partial differential equations, which means that both the time and space variables are included in the dynamic behavior of each agent. First, with a directed graph, an adaptive boundary controller is developed under boundary measurements, which can effectively reduce the control cost with dynamic control gains and a few actuators and sensors installed at the boundary of the spatial domain. Then, through the designed adaptive boundary controller, the linear matrix inequality (LMI)-based consensus conditions are obtained to ensure the exponential stability of the consensus error systems derived by utilizing the inequality techniques and Lyapunov direct approach. Lastly, two numerical examples demonstrate the effectiveness of the presented adaptive boundary control protocols.
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基于自适应边界控制的PDEs非线性不确定延迟多智能体系统的一致性
在非线性、时变延迟和不确定性的影响下,研究了用偏微分方程建模的多智能体系统的一致性问题,即每个智能体的动态行为中都包含了时间和空间变量。首先,利用有向图,在边界测量条件下开发了自适应边界控制器,利用动态控制增益和在空间域边界处安装少量致动器和传感器,有效降低了控制成本;然后,通过设计的自适应边界控制器,得到基于线性矩阵不等式(LMI)的一致性条件,以保证利用不等式技术和Lyapunov直接方法得到的一致性误差系统的指数稳定性。最后,通过两个算例验证了所提自适应边界控制协议的有效性。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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