Event-Triggered Model-Free Adaptive Formation Constrained Control for Nonlinear Heterogeneous Multiagent Systems

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2025-04-25 DOI:10.1109/TCYB.2025.3557383
Weiming Zhang;Dezhi Xu;Yujian Ye;Wei Hua;Bin Jiang
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Abstract

This article aims to address the formation control issue of the unknown nonaffine nonlinear heterogeneous multiagent system (MAS) considering formation tracking accuracy and computational cost. A novel dynamic prescribed boundary-based event-triggered mechanism is proposed first to flexibly adjust the emphasis on these two indicators, and applied to data modeling and controller design simultaneously to reduce their computational cost. On one hand, an observer-based pseudo gradient estimation algorithm is designed under event-triggered framework for model reconfiguration with only input/output data of system rather than mathematical dynamics. On the other hand, an event-triggered constrained control strategy is developed with several modules to cope with complex scenarios. Concretely, a data-driven anti-windup compensator is designed in case of input constraint, and an improved prescribed performance-based fractional order terminal sliding mode controller is explored for enhancement of the formation tracking accuracy and robustness of the controlled MAS with rigorous stability analysis. Both numerical simulation and hard-in-the-loop experiment on distributed energy storage systems are performed to attest the efficacy of the proposed formation control strategy.
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非线性异构多智能体系统事件触发无模型自适应编队约束控制
本文研究了未知非仿射非线性异构多智能体系统(MAS)的群体控制问题,同时考虑了群体跟踪精度和计算成本。首先提出了一种新的基于动态规定边界的事件触发机制,灵活调整这两个指标的重点,并将其同时应用于数据建模和控制器设计中,以降低其计算成本。一方面,在事件触发框架下,设计了一种基于观测器的伪梯度估计算法,用于仅利用系统的输入/输出数据而不考虑数学动态的模型重构;另一方面,开发了一种由多个模块组成的事件触发约束控制策略,以应对复杂的场景。具体而言,在输入约束情况下,设计了数据驱动的抗上卷补偿器,并探索了一种改进的基于规定性能的分数阶终端滑模控制器,通过严格的稳定性分析,提高了被控MAS的编队跟踪精度和鲁棒性。对分布式储能系统进行了数值模拟和硬环实验,验证了该编队控制策略的有效性。
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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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