A Novel ANSMC Algorithm for Tracking Control of 3-DOF Planar Parallel Manipulators

— Our article mainly focuses on dealing with several limitations of conventional sliding mode control (SMC), proportional-integral-derivative SMC (PID-SMC), and integral SMC (ISMC) for 3-DOF robotic manipulators at the same time. The paper focuses on three main points: improving the control accuracy, reducing chattering phenomena, and the convergence speed of the system states. Therefore, we develop a novel adaptive neural sliding mode control (ANSMC) algorithm for 3-DOF parallel robotic manipulators which has a complicated dynamic model, including modeling uncertainties, frictional uncertainties, and external disturbances. The control method is designed from three main control techniques, including ISMC, Radial Basis Function Neural Network (RBFNN), and the adaptive technique. First, a new integral terminal sliding mode (ITSM) surface is proposed to enhance the response rate and convergence rate. Second, RBFNN is employed to address disturbances and uncertainties. Besides, RBFNN also plays the role in reducing chattering behavior. While the adaptive technique is integrated into the reaching control law to remove the need for the upper bound values. Consequently, the proposed control system provides a high tracking accuracy and fast convergence rate. The chattering phenomena are significantly diminished in control signals. Simulation results on a 3-DOF parallel manipulator have confirmed the effectiveness of the proposed control method.