| Summary: | 碩士 === 國立臺北科技大學 === 自動化科技研究所 === 105 === This study presents an intelligent sliding mode controller (ISMC) to control a 6-DOF manipulator. Here, the recurrent Chebyshev Neural Network Estimator (RCNN) is used to estimate the external disturbances and parameter uncertainties, and a robust controller is further used to enhance the robustness of the proposed controller. The dynamics of the 6-DOF manipulator is a non-linear system and the dynamics of some joints are coupled with other joints. The traditional sliding mode control is often applied in this 6-DOF manipulator to robustly track the desired position and speed. However, the switching force experiences undesirable phenomenon of oscillations having finite frequency and amplitude, which is known as ‘chattering’. The chattering could be eliminated through a continuous approximation of the switching control in a boundary layer around the sliding surface; the saturation function is the typical one. For the above sliding mode control methods, the boundary of external disturbances and parameter uncertainties should be known, this is very difficult in practices. Therefore, an intelligent sliding mode control system which involved RCNN estimator to estimate the unknown external disturbance and parameter uncertainty is proposed to accurately track the position and velocity of the 6-DOF manipulator. The simulation results further verify the control performance of proposed ISMC.
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