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.

Department(s)

Electrical and Computer Engineering

Second Department

Computer Science

Comments

National Science Foundation, Grant None

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

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