Active Control of Chatter Vibrations in a Turning Process Using an Adaptive Fxlms Algorithm

In this paper a 2-DOF lumped mass model is used for dynamic modelling of a turning process. The cutting forces are modelled using predictive machining theory based on the Merchant cutting force model. Cutting parameters such as shear angle are calculated using experimental relations. Variation of cutting angles is also considered. Regarding the governing delayed differential equations, the model is simulated in the time domain using a Matlab/Simulink program. There is a good agreement between simulation results and the simulated and experimental results obtained by Xiao et al. [1]. Then, chatter vibration is suppressed using a single channel feedback FXLMS control method. The adaptive FIR filter generates proper canceller signals for the piezoactuators to reduce tool vibrations. The control method has the advantage of considering the statistical vibration of the cutting process that would be rarely considered in other active control methods. By using adaptive filters, it is possible for the controller to always be in the optimum condition by changing the FIR filter coefficients based on measured error signals. A significant reduction in vibration amplitude of the tool is achieved by using this active vibration control method. The response of the controller is observed for different actuator positioning. In addition, the performance of this control method is evaluated in the presence of disturbances in the vibration signals.