Set‐based fault detection and isolation for detectable linear parameter‐varying systems |
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| Authors: | Daniel Silvestre Paulo Rosa João P. Hespanha Carlos Silvestre |
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| Affiliation: | 1. Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China;2. Institute for Systems and Robotics, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal;3. Deimos Engenharia, Lisbon, Portugal;4. Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA |
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| Abstract: | In the context of fault detection and isolation of linear parameter‐varying systems, a challenging task appears when the dynamics and the available measurements render the model unobservable, which invalidates the use of standard set‐valued observers. Two results are obtained in this paper, namely, using a left‐coprime factorization, one can achieve set‐valued estimates with ultimately bounded hyper‐volume and convergence dependent on the slowest unobservable mode; and by rewriting the set‐valued observer equations and taking advantage of a coprime factorization, it is possible to have a low‐complexity fault detection and isolation method. Performance is assessed through simulation, illustrating, in particular, the detection time for various types of faults. Copyright © 2017 John Wiley & Sons, Ltd. |
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| Keywords: | fault detection and isolation unobservable LPV coprime factorization distributed |
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