Backstepping-based distributed abnormality localization for linear parabolic distributed parameter systems

被引：47
作者：
Feng, Yun [1 ,2 ]
Wang, Yaonan [1 ,2 ]
Wang, Jun-Wei [3 ]
Li, Han-Xiong [4 ]
机构：
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
[2] Hunan Univ, Natl Engn Lab Robot Visual Percept & Control Tech, Changsha 410082, Hunan, Peoples R China
[3] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
[4] City Univ Hong Kong, Dept Adv Design & Syst Engn, Kowloon, Hong Kong, Peoples R China
来源：
AUTOMATICA | 2022年 / 135卷
基金：
北京市自然科学基金;
关键词：
Distributed parameter systems; Fault detection; Fault localization; ACTUATOR FAULT ISOLATION; DESIGN;
D O I：
10.1016/j.automatica.2021.109930
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Abnormality localization for industrial processes described by distributed parameter systems (DPSs) is vital but seldom studied to the best of our knowledge. In this paper, a systematic framework is proposed to address this problem for a class of linear parabolic DPSs using a limited number of in-domain measurements plus one boundary measurement rather than the full-state measurement. The proposed methodology consists of an abnormality detection filter (ADF) and an abnormality localization filter (ALF) design based on the backstepping techniques and eigenspectrum. For the detection purpose, the residual is evaluated in a lumped manner; For the localization purpose, a distributed residual is first constructed and then evaluated in a distributed manner. Numerical simulations on a heat transfer rod are conducted to demonstrate the effectiveness of the proposed method. (C) 2021 Elsevier Ltd. All rights reserved.
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页数：9
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