RBF Network Adaptive Control of SCARA Robot Based on Fuzzy Compensation

Abstract Facing the requirements of high-precision control of SCARA robot systems in assembly and handling, RBF network adaptive control method based on fuzzy compensated SCARA robots is proposed. First, a SCARA robot dynamics model is established and theoretically analyzed based on Newton’s Euler equations. Second, the RBF network is used to approximate the ideal nominal model. Then, the fuzzy compensator is used to modify the friction, disturbance, load of the system and other external factors to compensate; finally, MATLAB/Simulink software was used to simulate the effect of SCARA robot system with and without fuzzy compensator. Experimental research shows that the control accuracy of SCARA robot joints with fuzzy compensators has been improved by 43.42%, 67.47% and 65.41%, respectively. The research results can provide some guidance for the precise assembly and handling of SCARA robots in production.