Active-Model-Based Fault Tolerant Control against Actuator Failures for Mobile Robot

Abstract

A novel fault-tolerant control method for autonomous mobile robot is proposed in this paper. The actuator effectiveness factors (AEFs) are introduced into the dynamics equation of mobile robot. The Unscented Kalman Filter (UKF) is employed for real time estimation of both the motion states and the AEFs. Such an active estimation is further incorporated into inverse dynamics control (IDC). The IDC enhanced by real time AEF feedback can achieve a robust tracking performance even with the occurrence of actuator failures. Extensive simulations are conducted with respect to the dynamics of a developed omini-directional mobile robot to verify the proposed scheme. The convergence of UKF-based estimation is presented in the presence of both noise-corrupted sensory data and rapidly changing states/AEFs. Performance of the IDC enhanced by the active estimation is also compared with that of the normal IDC based on fixed dynamics, to demonstrate the improvements of the proposed control scheme.