一类非线性代数微分参数变化系统的故障估计

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

European Journal of Control Pub Date : 2024-07-11 DOI:10.1016/j.ejcon.2024.101087

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引用次数: 0

摘要

本文介绍了一种同时估计描述符非线性参数变化系统的状态变量和致动器故障的方法。这类系统由插值参数变化线性部分和 Lipschitz 非线性部分组成。面对参数不确定性，所提出的观测器结构具有一定的鲁棒性和稳态精度。用 LMI（线性矩阵不等式）给出了存在性和稳定性的条件。所获得的结果在带有两个逆流单元模型的热交换器系统中进行了说明，该模型带有致动器故障。

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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Fault estimation for a class of nonlinear algebro-differential parameter-varying systems

This paper presents a methodology to simultaneous estimate state variables and actuator fault for descriptor nonlinear parameter-varying systems. This class of systems is composed of an interpolated parameter-varying linear part and Lipschitz nonlinear one. The proposed observer structure allows some robustness and steady state accuracy in face to parametric uncertainties. The conditions of existence and stability are given in terms of LMIs (Linear Matrix Inequalities). The obtained results are illustrated on the heat exchanger system with two countercurrent cells model with actuator fault.

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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.