Fuzzy adaptive control of coal gangue sorting parallel robot with variable load

Abstract

Delta parallel robot is widely used in the high-speed sorting industry with a light load and constant load. Its motion control is based on kinematic planning, without considering the influence of load and disturbance. The gangue sorting robot has the characteristics of a large load and random mass change, so traditional kinematics planning can not meet the control requirements. A fuzzy adaptive robust control algorithm is proposed to solve the problems of unstable motion and jitter in the coal gangue sorting robot. By establishing the mathematical model of the fuzzy system, the uncertain terms of the dynamic parameters caused by the random changes in the load are approximated. At the same time, to reduce the number of fuzzy rules and the amount of fuzzy calculation, the uncertain terms are decomposed into velocity terms and acceleration terms and then approximated, respectively. The Lyapunov analysis of the system is carried out, and the convergence of the system is proved. The simulation results show that the fuzzy adaptive robust control algorithm has a smaller error and faster convergence compared with the computational torque control algorithm when the system is sorting gangue within 8 kg, which improves the stability of gangue grasping.