Data-driven event-triggering mechanism for linear systems subject to input saturation

IF 2.5 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control Pub Date : 2024-11-01 DOI:10.1016/j.ejcon.2024.101045

Alexandre Seuret , Sophie Tarbouriech

引用次数: 0

Abstract

This paper focuses on designing an event-triggering mechanism aimed at reducing control updates while maintaining the stability of a saturated closed-loop system. It addresses the regional stabilization of linear systems under input saturation conditions from a data-driven perspective. To do so, we propose a systematic method to convert model-driven conditions into data-driven control design Linear Matrix Inequality (LMI) conditions, enabling the co-design of the event-triggering rule and the state feedback gain. The theoretical contribution is then applied to the control of a spacecraft rendezvous problem.

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输入饱和线性系统的数据驱动事件触发机制

本文的重点是设计一种事件触发机制，旨在减少控制更新，同时保持饱和闭环系统的稳定性。它从数据驱动的角度探讨了输入饱和状态下线性系统的区域稳定问题。为此，我们提出了一种系统方法，将模型驱动条件转换为数据驱动控制设计的线性矩阵不等式（LMI）条件，从而实现事件触发规则和状态反馈增益的共同设计。理论贡献随后被应用于航天器交会问题的控制。

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

European Journal of Control 工程技术-自动化与控制系统

CiteScore

5.80

自引率

5.90%

发文量

131

审稿时长

1 months

期刊介绍： The European Control Association (EUCA) has among its objectives to promote the development of the discipline. Apart from the European Control Conferences, the European Journal of Control is the Association''s main channel for the dissemination of important contributions in the field. The aim of the Journal is to publish high quality papers on the theory and practice of control and systems engineering. The scope of the Journal will be wide and cover all aspects of the discipline including methodologies, techniques and applications. Research in control and systems engineering is necessary to develop new concepts and tools which enhance our understanding and improve our ability to design and implement high performance control systems. Submitted papers should stress the practical motivations and relevance of their results. The design and implementation of a successful control system requires the use of a range of techniques: Modelling Robustness Analysis Identification Optimization Control Law Design Numerical analysis Fault Detection, and so on.