Edge-based event-triggered output feedback control for stochastic multi-agent systems

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-08-21 DOI:10.1002/acs.3878

Chuanxi Zhu, Beibei Chang

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引用次数: 0

Abstract

This article considers the problem of edge-based event-triggered output feedback control for linear multi-agent systems (MASs) with state-independent process and measurement noise under undirected communication topologies. The main breakthroughs are the design of distributed event-triggered output feedback control strategy and the stochastic stability analysis. Toward this, first, according to Kalman filtering theory, An observer is contrasted to optimally estimate the state of each agent. Next, a novel edge-based event-triggered mechanism (EBETM) is designed to reduce the communication frequency among agents effectively, and a positive interval between events is enforced in EBETM, which can eliminate the Zeno behavior. Then, stability of the estimation error and the consensus error systems is analyzed, the execution error is estimated and the almost sure consensus is achieved. Finally, a numerical example is given to show that MASs achieves almost sure consensus and there is a positive interval between the events of all edges.

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基于边缘事件触发的随机多代理系统输出反馈控制

摘要本文探讨了在无向通信拓扑结构下，对具有状态无关过程和测量噪声的线性多代理系统（MAS）进行基于边缘的事件触发输出反馈控制的问题。主要突破在于分布式事件触发输出反馈控制策略的设计和随机稳定性分析。为此，首先，根据卡尔曼滤波理论，对比了一个观测器来优化估计每个代理的状态。其次，设计了一种新颖的基于边缘的事件触发机制（EBETM），以有效降低代理之间的通信频率，并在 EBETM 中强制执行事件之间的正间隔，从而消除 Zeno 行为。然后，分析了估计误差和共识误差系统的稳定性，估计了执行误差，并实现了几乎确定的共识。最后，举例说明了 MASs 可以实现几乎确定的共识，并且所有边的事件之间都有正间隔。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.