Minimum entropy fault tolerant control for non-Gaussian singular stochastic distribution system

• 1、School of Electrical Engineering, Zhengzhou University,Henan Zhengzhou 450001
• 2、School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001

Abstract：This paper presents a new fault diagnosis (FD) and fault tolerant control (FTC) algorithm for a discrete-time non-Gaussian singular stochastic distribution control (SDC) system. Different from general SDC systems, the difficulty increases in the FD and FTC design of the singular SDC system as the relationship between the weights and the control input is expressed by a singular state space mode. In this paper, an adaptive observer is used to diagnose the fault of singular system. Furthermore, the gain of the observer and adaptive updated law can be formulated from the linear matrix inequality (LMI) approach. Entropy is used to represent the output randomness of the non-Gaussian stochastic systems when the target probability density function (PDF) is not known in advance. Based on the estimated fault information, the controller is reconfigured by minimizing the performance function with regard to the entropy subject to mean constraint. The reconfigured controller can make the post-fault SDC system still maintain good performance, leading to minimum entropy FTC of non-Gaussian singular SDC system. Computer simulations are given to demonstrate the validity of the fault diagnosis and minimum entropy FTC algorithms.

Keywords： Singular SDC system Minimum entropy Fault tolerant control Probability density function