Robust fault detection and estimation in nonlinear systems with unknown constant time-delays
type: Item
instance of: scholarly article
title: Robust fault detection and estimation in nonlinear systems with unknown constant time-delays
zbMATH Open document ID: 1426.93090
DOI: 10.1155/2017/4324370
author: Wenxu Yan
author: Dezhi Xu
author: Qikun Shen
published in: Mathematical Problems in Engineering
publication date: 2018-11-05T00:00:00Z
review text: Summary: This paper studies the problem of fault detection and estimation in nonlinear time-delayed systems with unknown inputs, where the time-delays are supposed to be constant but unknown. A new fault detection filter, which can estimate online the time-delays, is first introduced. Then, a reference residual model is proposed to formulate the robust fault detection filter design problem as an \(H_{\infty}\) model-matching problem. Furthermore, by a novel robust adaptive fault estimation algorithm, the classical assumption that the time derivative of the output error should be known is removed. In addition, applying a robust \(H_{\infty}\) optimization control technique, sufficient conditions for the existence of the fault detection filter (FDF) are derived in terms of linear matrix inequality (LMI). Finally, simulation results are presented to illustrate the effectiveness of the proposed algorithm.
Mathematics Subject Classification ID: 93B36
Mathematics Subject Classification ID: 93C40
Mathematics Subject Classification ID: 93B51
zbMATH DE Number: 6972098
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/4324370
OpenAlex ID: W2743537479
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description: scientific article; zbMATH DE number 6972098