A barrier function-based fixed-time fractional order sliding mode super-twisting control for robotic manipulators with actuator faults

Abstract

Considering the uncertainties, chattering, and actuator faults that may result in unexpected performance, this research proposes a fractional fixed-time super-twisting control scheme for robotic manipulators subject to uncertainties and faults without the need for disturbance observers. A novel fractional-order sliding manifold is first constructed to achieve accelerated convergence. Then, a modified super-twisting algorithm (STA) with a higher-order correction term is introduced to mitigate chattering and further enhance the convergence speed. In addition, an adjustable barrier function (ABF) is developed to relax the requirement of constant bounds for fault information and disturbances, since the growth of the upper bound is only related to the sliding variable. The parameters of the ABF regulate its rate of change, preventing excessive control magnitude that commonly appears in traditional barrier functions. The system stability is analyzed via Lyapunov theory to guarantee fixed-time convergence. Finally, numerical simulations and validations confirm the robustness and effectiveness of the proposed strategy.