Machining vibration is one of the most important constraints on productivity. This vibration may cause increase in machining costs, lower accuracy of products, and decrease tool life. Active control is one of the conventional methods for dealing with vibration in machining, but designing an optimized controller for machining process due to unknown parameters in the system is challenging. DVF control method with low computational costs and high capability in increasing the performance of the cutting tool is an effective method, but due to increasing in actuator control input, it can cause actuator saturation; thus, it is not an efficient control method. The aim of this research is implementation of a nonlinear fractional PID controller for increasing effectiveness and improving performance of active vibration control on a boring bar. The results of impact control tests indicate that nonlinear PID control algorithm has good performance in reducing vibrations and increasing the damping of the structure. Using the controller performance criteria, the optimal fractional can be chosen for the nonlinear PID controller, which in addition to increasing the damping of the tool, can reduce the power consumption and, thus, prevent the actuator saturation. The results of the cutting tests also show that the nonlinear PID controller reduces control voltage and actuator power with respect to the DVF controller, which results in improving the boundaries of stable machining. Moreover, during impacts in machining process, such as the initial engagement of the tool, the proposed controller results in a significant reduction in the control voltage peak.

In this paper, a new active vibration control system has been proposed for the elimination of boring bar chatter in the internal turning process. The system is composed of a boring bar equipped with electromagnetic actuator and accelerometer, as well as a novel adaptive control algorithm that is widely used in the field of active noise control. The controller is known as feedback FxNLMS and is composed of two finite impulse response adaptive filters. One of the filters is known as a model filter, which predicts the dynamic model of actuator-boring bar assembly. The other is known as the control filter and anticipates the inverse model of forwarding path dynamics. The weight vector of the adaptive filter is adjusted by using the normalized least mean square algorithm. Firstly, the impact test is conducted in the presence of an adaptive controller. It is observed that the magnitude of the dominant mode on the forward path’s frequency response function is drastically suppressed by 36 dBs. Secondly, the internal turning tests are conducted on Aluminum alloy 6063-T6, to investigate the performance of the adaptive controller for the purpose of chatter mitigation. Due to the optimal performance of the adaptive controller, the dominant magnitude of the boring bar’s power spectral density is successfully attenuated up to 68 dBs, and the critical limiting depth of cut is increased by 10 folds. Also, the roughness of the machined surface is remarkably improved by 8 folds compared to the control-off cutting test. Moreover, the actuator cost is considerably reduced by 3 folds in comparison to the optimal constant-gain integral controller.