Fault diagnosis of mobile robot based on variable structure multiple model algorithm

Fast and accurate fault diagnosis method is important for mobile robot´s fault tolerant control and repairing. The traditional method may influence the accuracy of fault diagnosis when the system has a large model set because of the model competition. Traditional method generally use the extended Kalman filter which has a law calculation accuracy. In this paper, combining the variable structure multiple model algorithm(VSMM) with the unscented Kalman filter(UKF) not only can solve the model competition caused by the combined fault which leads to a large number of fault models, but also can solve the problem of low calculation accuracy caused by traditional extended Kalman filter(EKF) used in nonlinear systems. The simulation results show that this method effectively improves the response time and the accuracy of fault diagnosis of mobile robot.