Abstract
In this paper, a novel, unified model-Based fault-detection and prediction (FDP) scheme is developed for nonlinear multiple-input multiple-output (MIMO) discrete-time systems. the proposed scheme addresses both state and output faults by considering separate time profiles. the faults, which could be incipient or abrupt, are modeled using input and output signals of the system. the fault-detection (FD) scheme comprises online approximator in discrete time (OLAD) with a robust adaptive term. an output residual is generated by comparing the FD estimator output with that of the measured system output. a fault is detected when this output residual exceeds a predefined threshold. Upon detecting the fault, the robust adaptive terms and the OLADs are initiated wherein the OLAD approximates the unknown fault dynamics online while the robust adaptive terms help in ensuring asymptotic stability of the FD design. using the OLAD outputs, a fault diagnosis scheme is introduced. a stable parameter update law is developed not only to tune the OLAD parameters but also to estimate the time to failure (TTF), which is considered as a first step for prognostics. the asymptotic stability of the FDP scheme enhances the detection and TTF accuracy. the effectiveness of the proposed approach is demonstrated using a fourth-order MIMO satellite system. © 2010 IEEE.
Recommended Citation
B. T. Thumati and S. Jagannathan, "A Model-Based Fault-detection and Prediction Scheme for Nonlinear Multivariable Discrete-time Systems with Asymptotic Stability Guarantees," IEEE Transactions on Neural Networks, vol. 21, no. 3, pp. 404 - 423, article no. 5398833, Institute of Electrical and Electronics Engineers, Mar 2010.
The definitive version is available at https://doi.org/10.1109/TNN.2009.2037498
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Asymptotic stability; Fault detection (FD); Multiple-input- multiple-output (MIMO) nonlinear discrete-time system; Prognostics
International Standard Serial Number (ISSN)
1045-9227
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Mar 2010
PubMed ID
20106734
Comments
National Science Foundation, Grant None