Adaptive PID Control of Fast Tool Servo Based on Neural Network

To improve the control performance of FTS(fast tool servo),reduce the following error and achieve the fabrication of sinusoidal grid surface,an adaptive PID control method was brought out based on RBF(Riverbank filtration) and BP(Backpropagation) neural networks.This method can improve the tracing accuracy of FTS and then reduce the shape error of the fabricated surface.From the simulation results,it can be seen that by adopting this control algorithm,the maximum tracing error is 1.37μm,and the average tracking error is 0.52μm,each reduced by 28% and 40%.