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

被引：0

作者：

Zhang, Xu ^{[1
]}

Luo, Biao ^{[1
]}

Wang, Zi-Peng ^{[2
,3
]}

Xu, Xiaodong ^{[1
]}

Yang, Chunhua ^{[1
]}

机构：

[1] Cent South Univ, Sch Automat, Changsha 410083, Peoples R China

[2] Beijing Univ Technol, Sch Informat Sci & Technol, Beijing Lab Smart Environm Protect, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China

[3] Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China

来源：

IEEE TRANSACTIONS ON CYBERNETICS | 2025年 / 55卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Consensus control; Adaptation models; Mathematical models; Vehicle dynamics; Delays; Delay effects; Actuators; Uncertainty; Switches; Multi-agent systems; Adaptive control; boundary control; consensus control; linear matrix inequality (LMI); multiagent systems (MAS); time-varying delay; DISTRIBUTED-PARAMETER MODELS; STABILITY;

D O I：

10.1109/TCYB.2025.3554844

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：2980 / 2992

页数：13

共 42 条

[1] Multi-Agent System in Urban Traffic Signal Control [J].