A new fault tolerant strategy using adaptive time delay estimation for robot manipulators with actuator faults

In actual industrial production, the actuator of manipulators may fall into a faulty state due to overloading, temperature changes, disturbances and other factors, resulting in the expected tasks cannot be accomplished effectively. In this paper, we propose a new adaptive time-delay estimation fault-tolerant method for the trajectory tracking problem of manipulator systems with actuator faults. The proposed approach can quickly recover the control performance and effectively suppress the growth of steady state error. We design a novel adaptive gain law utilizing error feedback that can effectively reduce the effects of faults by rapidly adjusting the control gain after actuator faults. The model uncertainty is handled by introducing a time delay estimation strategy. Additionally, the stability of the closed-loop system under the proposed method is guaranteed by theoretical analysis. By comparing the simulation results with the traditional adaptive fault-tolerance methods, the superiority of the proposed method in terms of performance recovery after actuator faults is demonstrated.