In this article, adaptive inverse control of chatter vibrations in internal turning process is addressed. The active boring bar is composed of a slender steel cutting tool, an electrodynamic shaker as controllable actuator and an IEPE accelerometer as feedback sensor. The SISO control system actuates in the direction normal to the cut surface. A novel adaptive inverse control algorithm is presented in this paper. This algorithm is mainly used in the feed-forward Active Noise Control (ANC) applications and is known as the Filtered-x Normalized Least Mean Square (FxNLMS). In order to extend the application of adaptive inverse control algorithms in the field of Active Vibration Control (AVC), the FxNLMS algorithm with feedback architecture is suggested for the specific problem of chatter suppression in internal turning operations. The performance of developed adaptive feedback controller is experimentally verified during the internal turning of Aluminum alloy 6063-T6. The value of critical limiting depth of cut is anticipated to be nearly 0.2 [mm] for the slender boring bar. However, the stable cutting process is conducted by the active boring bar in the presence of adaptive controller up to depth of cut 2 [mm]. That is, the boundary of stability is enhanced by at least 10 folds. It has been observed that the amplitude of chatter vibrations is efficiently suppressed adjacent to the fundamental resonance peak of the active boring bar. In addition, the feedback FxNLMS controller effectively attenuates the boring bar’s vibration by at least 70 dBs. Moreover, the periodic chatter marks are eliminated from the surface texture of workpiece and the roughness of cut surface is remarkably improved. The obtained results suggest that the practical application of adaptive inverse control algorithms for chatter rejection can be extended to other machining processes as well.

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