Adaptive fuzzy finite-time control of robotic manipulator: a command filter-based sliding mode approach

In this paper, a finite-time command filter-based sliding mode fault-tolerant control (FTCFSMFTC) strategy is developed for uncertain robotic manipulator systems (RMS) with actuator faults (AFs) under interval excitation (IE) conditions. A novel adaptive control algorithm is introduced via integrating the command filter backstepping with sliding mode control in a completely new way, in which the error compensation mechanism of traditional command filter backstepping is eliminated and a fresh integral terminal sliding surface is provided based on system information and the filter output; also, a composite optimal weight estimation method is designed for the unknown dynamics and AFs in RMS. Then, by the FTCFSMFTC law, all signals of RMS are finite-time (FT) bounded, and the trajectory tracking error converges to zero in FT under IE conditions. Finally, the effectiveness of the proposed algorithm is validated through simulation experiments.