Fault isolation and fault‐tolerant control for nonlinear stochastic distribution control systems with multiplicative faults

In this paper, a fault isolation, diagnosis and fault tolerant control algorithm is proposed for nonlinear multiple multiplicative faults stochastic distribution control systems employing Takagi–Sugeno fuzzy system. To obtain the detailed fault information, a fault detection algorithm is introduced...

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Bibliographic Details
Published in:International journal of robust and nonlinear control Vol. 33; no. 11; pp. 6070 - 6086
Main Authors: Kang, Yunfeng, Yao, Lina, Zhou, Jinglin, Wang, Hong
Format: Journal Article
Language:English
Published: Bognor Regis Wiley Subscription Services, Inc 25.07.2023
Wiley
Subjects:
Algorithms
Control algorithms
Control systems
Control theory
ENGINEERING
Fault detection
Fault diagnosis
fault estimation
fault isolation
Fault tolerance
fault-tolerant control
Faults
model predictive control
multiplicative faults
Nonlinear control
nonlinear stochastic distribution control systems
Predictive control
Probability density functions
Probability theory
Subsystems
ISSN:1049-8923, 1099-1239
Online Access:Get full text
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Summary:In this paper, a fault isolation, diagnosis and fault tolerant control algorithm is proposed for nonlinear multiple multiplicative faults stochastic distribution control systems employing Takagi–Sugeno fuzzy system. To obtain the detailed fault information, a fault detection algorithm is introduced to discover the fault occurrence time. Then a fault isolation observer is built to produce the residual, and the error system is separated to subsystems affected only by disturbance and multiplicative faults. Moreover, a fault estimation scheme is presented to obtain the fault magnitude information. When faults occur, the system output probability density function will deviate from the desired distribution. So the model predictive control fault tolerant control scheme is needed to minimize the impact of faults as much as possible to make sure that the post fault output probability density function track the desired probability density function. The validity of the designed algorithm is demonstrated through a simulation example, where the fault tolerant control algorithm ensures that the system output probability density function still track the given output probability density function despite the complex case of multiple multiplicative faults occurring simultaneously.
Bibliography:Corrections added on 17 April 2023, after first online publication: the affiliation links of authors Jinglin Zhou and Hong Wang in the author byline have been corrected in this version.
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USDOE
AC05-00OR22725
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.6682