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Entropy 2017, 19(5), 218; doi:10.3390/e19050218

Minimum Entropy Active Fault Tolerant Control of the Non-Gaussian Stochastic Distribution System Subjected to Mean Constraint

School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
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Academic Editor: Kevin H. Knuth
Received: 23 March 2017 / Revised: 24 April 2017 / Accepted: 3 May 2017 / Published: 11 May 2017
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Abstract

Stochastic distribution control (SDC) systems are a group of systems where the outputs considered is the measured probability density function (PDF) of the system output whilst subjected to a normal crisp input. The purpose of the active fault tolerant control of such systems is to use the fault estimation information and other measured information to make the output PDF still track the given distribution when the objective PDF is known. However, if the target PDF is unavailable, the PDF tracking operation will be impossible. Minimum entropy control of the system output can be considered as an alternative strategy. The mean represents the center location of the stochastic variable, and it is reasonable that the minimum entropy fault tolerant controller can be designed subjected to mean constraint. In this paper, using the rational square-root B-spline model for the shape control of the system output probability density function (PDF), a nonlinear adaptive observer based fault diagnosis algorithm is proposed to diagnose the fault. Through the controller reconfiguration, the system entropy subjected to mean restriction can still be minimized when fault occurs. An illustrative example is utilized to demonstrate the use of the minimum entropy fault tolerant control algorithms. View Full-Text
Keywords: fault diagnosis; fault tolerant control; entropy; mean constraint; probability density function fault diagnosis; fault tolerant control; entropy; mean constraint; probability density function
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Jin, H.; Guan, Y.; Yao, L. Minimum Entropy Active Fault Tolerant Control of the Non-Gaussian Stochastic Distribution System Subjected to Mean Constraint. Entropy 2017, 19, 218.

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