Active Fault Detection Based on State Set-membership Estimation

被引：0
|
作者：
Wang J. [1 ]
Shi Y.-R. [2 ]
Zhou M. [1 ]
机构：
[1] School of Electrical and Control Engineering, North China University of Technology, Beijing
[2] College of Information Science and Technology, Beijing University of Chemical Technology, Beijing
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2021年 / 47卷 / 05期
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Active fault detection; Auxiliary input signal; Incipient fault; State set-membership estimation; Zonotope;
D O I：
10.16383/j.aas.c180830
中图分类号：
学科分类号：
摘要：
For modern complex systems, incipient faults is usually difficult to be detected. Under the assumption that system process disturbance and measurement noise are unknown but bounded, this paper proposes a novel active fault detection method based on state set-membership estimation. First, a zonotopic Kalman filter is designed to estimation systems states, and the state sets affected by the unknown inputs are described by zonotopes. Then, an auxiliary input signal is designed such that the state sets of the normal model are separated from the ones of faulty models, as a result, incipient faults are detected successfully. In order to decrease the effect of the auxiliary input to the practical systems, the minimum auxiliary input signal is required. In this paper, the optimization problem is transformed into a mixed integer quadratic programming problem. Compared with the output sets based auxiliary input signal design method, the proposed technique can achieve a smaller auxiliary input signal because of states set are not affect by the measurement noise at the next time instant, and it has less conservatism. Copyright © 2021 Acta Automatica Sinica. All rights reserved.
引用
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页码：1087 / 1097
页数：10
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