THIẾT KẾ VÀ THỰC HIỆN BỘ ĐIỀU KHIỂN HỆ TAY MÁY

Abstract

An adaptive sliding mode control (SMC) based on radial basis function neural network (RBFNN) is designed and implemented in this paper. The proposed controller is applied to a 2-degree-of-freedom manipulator that has been deployed in the construction materials manufacturing, metallurgy, mechanical engineering and shipbuilding industries. The adaptive SMC based on RBFNN is used to ensure the manipulator’s actual position follows the desired in a finite time. The stability of the system is proven by Lyapunov theory. Simulation results in MATLAB/Simulink show the effectiveness of the proposed controller with the rising time, the settling time, the percent overshoot, the steady state error of link 1 are 0.7708(s), 1.4254(s), 0.0559(%), 0(rad) and link 2 are 0.9253(s), 1.5655(s), 0.1138(%), 0(rad), respectively.