具有不稳定模式的开关系统的稳健故障检测:无缓冲转移分片滤波方法

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Zhanhong Liang, Jinfeng Gao, Lina Yao
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引用次数: 0

摘要

本研究解决了具有不稳定模式的开关系统中的无缓冲转移故障检测(FD)问题。通过分割每个停留时间间隔,开发了一种开关式片断 FD 滤波器作为残差信号发生器。不同滤波器之间的转换会在残差信号中产生明显的突然跳变。因此,我们引入了残差无缓冲传输性能的新定义,以限制切换期间残差波动的幅度。此外,还设计了一种交替切换策略,其特点是平均停留时间取决于慢速和快速模式,并得到多重不连续 Lyapunov 函数方法的支持,以确保增强系统的渐进稳定性和加权性能。同时,还以线性矩阵不等式的形式阐明了无缓冲传输 FD 问题可解性的充分条件。最后,介绍了一个开关降压-升压电路和一个数值示例,以证实所提出的无缓冲转移分片滤波方法的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust fault detection for switched systems with unstable modes: A bumpless transfer piecewise filtering approach

This investigation addresses the bumpless transfer fault detection (FD) problem within switched systems that possess unstable modes. A switched piecewise FD filter is developed as a residual generator by segmenting each dwell time interval. The transition between different filters precipitates pronounced, abrupt jumps in the residual signal. Consequently, a novel definition of the residual bumpless transfer performance is introduced to constrain the magnitude of residual fluctuations during switching instances. Additionally, an alternating switching strategy—characterized by slow and fast mode-dependent average dwell time and supported by the multiple discontinuous Lyapunov function method—is devised to assure the asymptotic stability and the weighted H $$ {H}_{\infty } $$ performance of the augmented system. Concurrently, sufficient conditions for the solvability of the bumpless transfer FD problem are articulated in the form of linear matrix inequalities. Lastly, a switched buck-boost circuit and a numerical example are presented to substantiate the merits of the proposed bumpless transfer piecewise filtering method.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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