Research on spray-paint robot position control system based on BP neural network

Abstract

The spray-paint robot is a nonlinear position control system. A self-adaptive PID (proportion-integral-differential) controller with BP (back propagation) neural network was designed for spray-paint robot. This controller took full advantages of PID control with simple arithmetic and neural network with good self-adaptive and anti-jamming ability, and by neural network's learning and on-line identification, adaptively adjusted PID control parameters that the control system could show good robustness and control performance to system parameter change. Simulation and experiments results prove that by making real-time adjustment on PID parameters, this system can obtain good tracking performance and greatly reduce the adjustment difficulty of the control system