Next Article in Journal
Ordered Regions within a Nonlinear Time Series Solution of a Lorenz Form of the Townsend Equations for a Boundary-Layer Flow
Previous Article in Journal
Quantitative Analysis of Dynamic Behaviours of Rural Areas at Provincial Level Using Public Data of Gross Domestic Product
Entropy 2013, 15(1), 32-52; doi:10.3390/e15010032
Article

Function Based Fault Detection for Uncertain Multivariate Nonlinear Non-Gaussian Stochastic Systems Using Entropy Optimization Principle

1,2,*  and 1
Received: 26 June 2012; in revised form: 16 December 2012 / Accepted: 18 December 2012 / Published: 21 December 2012
Download PDF [1113 KB, uploaded 21 December 2012]
Abstract: In this paper, the fault detection in uncertain multivariate nonlinear non-Gaussian stochastic systems is further investigated. Entropy is introduced to characterize the stochastic behavior of the detection errors, and the entropy optimization principle is established for the fault detection problem. The principle is to maximize the entropies of the stochastic detection errors in the presence of faults and to minimize the entropies of the detection errors in the presence of disturbances. In order to calculate the entropies, the formulations of the joint probability density functions (JPDFs) of the stochastic errors are presented in terms of the known JPDFs of both the disturbances and the faults. By using the novel performance indexes and the formulations for the entropies of the detection errors, new fault detection design methods are provided for the considered multivariate nonlinear non-Gaussian plants. Finally, a simulation example is given to illustrate the efficiency of the proposed fault detection algorithm.
Keywords: fault detection; multivariate stochastic systems; uncertain; entropy optimization; non-Gaussian system fault detection; multivariate stochastic systems; uncertain; entropy optimization; non-Gaussian system
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Yin, L.; Zhou, L. Function Based Fault Detection for Uncertain Multivariate Nonlinear Non-Gaussian Stochastic Systems Using Entropy Optimization Principle. Entropy 2013, 15, 32-52.

AMA Style

Yin L, Zhou L. Function Based Fault Detection for Uncertain Multivariate Nonlinear Non-Gaussian Stochastic Systems Using Entropy Optimization Principle. Entropy. 2013; 15(1):32-52.

Chicago/Turabian Style

Yin, Liping; Zhou, Li. 2013. "Function Based Fault Detection for Uncertain Multivariate Nonlinear Non-Gaussian Stochastic Systems Using Entropy Optimization Principle." Entropy 15, no. 1: 32-52.


Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert