In this paper, a novel dynamic model is proposed for an actively damped boring bar equipped with electromagnetic actuator. The dynamic models of actuator and boring bar are obtained by using the suggested systematic identification approach, which is based upon the fundamental tools and techniques of system identification theory. The electro-mechanical system or the forward path is consisted of 3 basic components, i.e. linear power amplifier, electrodynamic shaker, and boring bar structure. In this paper, the dynamic models of forward path’s sub-systems are simultaneously identified. The component-based identification approach has led to a remarkable finding about the source of nonlinearity in the dynamic model of forward path. According to the presented experimental observations, it has been concluded that electromagnetic actuator can be modeled as a linear dynamic system, while the boring bar structure exhibits nonlinear behavior, since the prediction accuracy of boring bar dynamic model is drastically reduced by changing the amplitude of excitation. As a result, a new parameter varying dynamic model is presented for describing the dynamic behavior of forward path in terms of both frequency and excitation level. The proposed dynamic model has a predefined representation with the least possible mathematical order. It can anticipate the time domain response of forward path due to chirp excitation with 88% accuracy. In addition, during the validation stage, the proposed model forecasts the dynamic response of system due to Gaussian white noise excitation with remarkable accuracy. Moreover, the dynamic model of electromagnetic actuator can predict the dynamic force signature of actuator with 85% accuracy.

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.