Fault detection for uncertain LPV systems using probabilistic set-membership parity relation
Name
2326-Fault-Detection-for-Uncertain-LPV-Systems-Using-Probabilistic-Set-membership-Parity-Relation.pdf
Description
Accepted version
Size
1.12 MB
Format
Adobe PDF
Checksum (MD5)
b114a16103ab8836a33b80c657fdcb7f
Author(s)
Wan, Yiming
Puig, Vicenç
Ocampo-Martinez, Carlos
Wang, Ye
Harinath, Eranda
Braatz, Richard D
Date Issued
2020
Journal
Journal of Process Control
Publisher
Elsevier BV
Version
Author's final manuscript
Abstract
© 2019 This paper considers fault detection of uncertain linear parameter varying systems that have polynomial dependence on parametric uncertainties. A conventional set-membership (SM) approach is able to ensure zero false alarm rate (FAR) by using conservative threshold sets, but usually results in a high missed detection rate (MDR) due to equally treating all uncertainty realizations without distinguishing between high and low probability of occurrence. To address this limitation, a probabilistic SM parity relation approach is proposed to exploit probabilistic information on the parametric uncertainties, which results in a reduced MDR by admitting an acceptable FAR. The parity relation is first polynomially parameterized with respect to uncertain parameters. Then, Gaussian mixtures are adopted to efficiently compute uncertainty propagation from stochastic uncertainties to the residual distribution. To achieve an acceptable FAR, a non-convex confidence set of residuals – represented by a union of ellipsoids – is determined for the consistency test. The effectiveness of the proposed approach is illustrated using a continuous stirred tank reactor example including performance comparisons with a deterministic zonotope-based method.
MIT Department
Massachusetts Institute of Technology. Department of Chemistry
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.JPROCONT.2019.12.010
