Simultaneous state and fault estimation for a class of nonlinear Markov jump systems by distributed fault-tolerant observers

Abstract

This paper investigates the estimation problem of a class of nonlinear Markov jump systems with actuator and sensor faults. The main goal is to design a distributed fault-tolerant observer to estimate system states and actuator faults simultaneously. Firstly, a novel distributed observer network is constructed to compensate the missing information of unobservable nodes of the system. Next, a class of new redundant sensors are set up on each distributed observer node to obtain more output measurement samples. More importantly, when some of the mentioned sensors occur faults, an index of sensor heath level is constructed to characterize the quality of the faulty sensor information. Further, a novel algorithm is designed to mask low quality output information and filter out relatively healthy one automatically. Based on the selected healthy output information, the system state and actuator fault are estimated in the case of sensor failure. Finally, an example is provided to demonstrate the effectiveness of the proposed method.