Please use this identifier to cite or link to this item: https://doi.org/10.1063/1.3106516
Title: A H-infinity fault detection and diagnosis scheme for discrete nonlinear system using output probability density estimation
Authors: Zhang, Y. 
Wang, Q.-G. 
Lum, K.-Y. 
Keywords: B-spline expansions
Fault detection and diagnosis
Filter design
Probability density function
Issue Date: 2009
Source: Zhang, Y.,Wang, Q.-G.,Lum, K.-Y. (2009). A H-infinity fault detection and diagnosis scheme for discrete nonlinear system using output probability density estimation. AIP Conference Proceedings 1107 : 79-84. ScholarBank@NUS Repository. https://doi.org/10.1063/1.3106516
Abstract: In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches. © 2009 American Institute of Physics.
Source Title: AIP Conference Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/68834
ISSN: 0094243X
DOI: 10.1063/1.3106516
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