Design of distributed event-triggered states and unknown disturbances observers for time-varying delay interconnected 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 : 2024-03-24 DOI:10.1002/acs.3796
Dinh Cong Huong
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Abstract

This article considers the problem of designing distributed event-triggered states and unknown disturbances observers for a class of nonlinear interconnected systems where the local state vectors are affected by unknown delays and the nonlinear function satisfying the Lipschitz condition. Distributed observers are designed based on the local input vector and both the local and remote output vectors. Different from previously distributed observers for interconnected systems where the local and remote output vectors are updated continuously, the one in this article uses only information on the local and remote output vectors updating at triggering instants of proposed event-triggered mechanisms. This indicates that the proposed method in this article is better than the existing ones in saving communication resources while still keeping an acceptable estimation performance. Sufficient conditions for the existence of the proposed distributed observers are established and are formed in a convex optimization problem which can be easily solved by using the MATLAB LMI Control Toolbox. Finally, a numerical example is given to confirm the effectiveness and advantages of the proposed method.

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为时变延迟互联系统设计分布式事件触发状态和未知干扰观测器
本文探讨了为一类非线性互连系统设计分布式事件触发状态和未知干扰观测器的问题,在这类系统中,本地状态向量受未知延迟和满足 Lipschitz 条件的非线性函数的影响。分布式观测器的设计基于本地输入向量以及本地和远程输出向量。与以往连续更新本地和远程输出矢量的互联系统分布式观测器不同,本文中的观测器仅在事件触发机制的触发时刻使用本地和远程输出矢量的更新信息。这表明本文提出的方法比现有方法更能节省通信资源,同时还能保持可接受的估计性能。本文建立了所提分布式观测器存在的充分条件,并将其形成一个凸优化问题,利用 MATLAB LMI 控制工具箱可以轻松解决该问题。最后,给出了一个数值示例,以证实所提方法的有效性和优势。
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来源期刊
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.
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