Abstract
This study presented an improved adaptive nonlinear terminal sliding mode control technique for the manipulator robot to achieve better adaptability and faster finite-time convergence. First, an adaptive self-updating algorithm will be developed to relax the problems of fixed control gain for the main proposed controller. Next, an adaptive neural network estimator is applied by estimating the robot dynamics to increase the tracking control performance. In addition, a compensator-typed robust controller also is designed to guarantee the robustness, continuity, and smoothing properties of the control system. To verify the effectiveness of the proposed method, besides applying the Lyapunov theorem, the comparative numerical simulation results will be provided in more detail.
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