Nonsingular Fast Terminal Sliding Mode Control of Uncertain Robotic Manipulator System Based on Adaptive Fuzzy Wavelet Neural Network

The nonsingular fast terminal sliding mode control (NFTSMC) problem of an uncertain robotic manipulator system based on the adaptive fuzzy wavelet neural network (AFWNN) is studied in this paper. First, a novel NFTSMC method is developed to achieve fixed-time tracking control of the robotic manipulator in the presence of parametric perturbation, external disturbances, and joint friction. Then, to address the adverse impacts of lumped uncertainties in the robotic manipulator system, a well-designed AFWNN algorithm is devised. Next, the tracking error system is proved to be fixed-time stable utilizing the Lyapunov function analysis method. Finally, the effectiveness and superiority of the NFTSMC strategy based on the AFWNN are verified by several comparative simulations.