切换拓扑下具有不匹配干扰的多代理系统的事件触发有限时间编队跟踪

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2024-08-01 DOI:10.1016/j.isatra.2024.05.031
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引用次数: 0

摘要

本文研究了切换拓扑结构下领导者-跟随者多代理系统(MAS)的编队跟踪问题。所考虑的系统在领导者和跟随者的动态过程中都会受到不匹配和匹配的干扰,这就对控制协议的鲁棒性提出了更高的要求。在存在扰动和领导者未知控制输入的情况下,首先设计了一种嵌入鲁棒项的创新型分布式观测器,用于在有限时间内估计领导者的状态。考虑到开关拓扑结构,提出了一种将收敛过程分为两个阶段的新型分析方案,以确定估计误差的有限时间(FT)收敛性。然后,利用构建的辅助变量,提出了一种具有事件触发机制的 FT 控制器,其中合理设计了多个鲁棒反馈项,以有效抑制不匹配和匹配干扰。因此,尽管存在扰动环境和开关拓扑结构,仍能在节省资源的情况下实现 FT 编队跟踪。仿真实例证实了所提算法的有效性。
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Event-triggered finite-time formation tracking of multi-agent systems with mismatched disturbances under switching topologies

The formation tracking of the leader–follower multi-agent systems (MASs) under switching topologies is investigated. The considered system is exposed to both the mismatched and matched disturbances in the dynamics of the leader and followers, which places higher requirements for the robustness of the control protocol. In the presence of disturbances and leader’s unknown control input, an innovative distributed observer embedded with robust terms is designed firstly to estimate leader’s states in finite time. Taking account of the switching topologies, a novel analysis scheme that divides the convergence process into two stages is proposed to establish the finite-time (FT) convergence of estimation errors. Then, by virtue of a constructed auxiliary variable, a FT controller with an event-triggered mechanism is put forward, in which multiple robust feedback terms are designed wisely to suppress the mismatched and matched disturbances effectively. As a result, the FT formation tracking can be achieved with saved resources, despite perturbed environments and switching topologies. Simulation examples are presented to confirm the effectiveness of the proposed algorithm.

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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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