Fault Diagnosis and Tolerant Control for Discrete Stochastic Distribution Collaborative Control Systems

This paper presents a novel fault-tolerant control method for a class of discrete-time and nonGaussian stochastic systems, where two subsystems are connected in series so as to operate in a collaborative way. For such systems, the output probability density function of the second subsystem is taken as the output of the whole system. The proposed method includes the design of a fault diagnosis (FD) algorithm for the first subsystem and the establishment of a fault-tolerant control algorithm for the second subsystem. At first, linear matrix inequality techniques are used to construct the FD algorithm for the first subsystem. Once the fault is diagnosed, a fault-tolerant control algorithm is designed using the well-known optimal norm-based iterative learning control approach. Different from the existing fault tolerant controller methods, the proposed fault-tolerant control is designed not for the faulty subsystem but for the healthy subsystem. As a result, when a fault occurs in the first subsystem, the reconfigured controller for the healthy second subsystem can accommodate the fault and guarantee that the whole system will still exhibit good operational performance. A simulated example is used to demonstrate the collaborative fault-tolerant control effect and desired results have been obtained.