RESUMO
In this study, a fractional order fast terminal sliding mode control strategy is developed to address the trajectory tracking problem that arises when robot manipulators are subjected to uncertainties and external disturbances. A novel fractional order fast terminal sliding surface is proposed to achieve rapid finite time convergence and the explicit expression for the settling time is also formulated. To manage uncertainties, chattering phenomenon, singularities, large control gains, etc., a new fractional order fast terminal sliding mode control scheme is developed based on the proposed sliding surface. The radial basis function neural network is used in the proposed control strategy to approximate the nonlinearities and modeling errors of the robot dynamics in real time. The reconstruction error of neural network and upper bound on disturbances are handled by the adaptive compensator. The Lyapunov technique is used to examine the stability of the proposed control strategy. The proposed control technique improves the efficiency of the controller and allows for the asymptotic error convergence to occur in a finite amount of time. To compare the effectiveness of the proposed scheme to various existing control approaches, numerical simulation studies are also conducted.
