Active vibration control of thin-walled milling based on ANFIS parameter optimization

In view of the time-varying dynamic characteristics of thin-walled milling, an optimization method of thin-walled milling control parameters based on the ANFIS system is proposed. Firstly, the control system strategy design and equipment selection construction were carried out, and the fuzzy inference model was built based on matlab platform; Subsequently, the fuzzy inference model of the thin-walled workpiece milling process was obtained by collecting fuzzy inference training data set of and the ANFIS system training. The proportional control coefficient of the controller was optimized based on the input and output relation of the model. Finally, the dynamic response and surface roughness of the controlled thin-walled panel milling process before and after optimization were obtained through cutting experiments, and the effectiveness of the ANFIS method to optimize the control parameters and the reliability of the fuzzy reasoning model were verified through analysis of the reasoning results. The results show that the ANFIS system can predict the vibration response performance of the target by setting the input and output reasonably, and optimize the related variable parameters according to the predicted results, so as to make the thin-wall milling system more stable.