Minimum entropy fault tolerant control for non-gaussian singular stochastic distribution system using rational square-root B-spline model

In this paper the rational square-root B-spline model is used to approximate the system output PDF and an adaptive observer is used to diagnose the fault of the singular stochastic distribution system. The gain of the observer and adaptive updated law can be formulated by solving the corresponding linear matrix inequality (LMI). Entropy is used to represent the output randomness of the non-Gaussian stochastic system 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 output of the post-fault SDC system still have minimum uncertainty, leading to the 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.