Experimental comparison of different automatically tuned control strategies for active vibration control

Abstract

Chatter is the main limiting factor affecting the material removal rates of machine tools and is caused by the machine's most flexible structural mode shapes. The use of active vibration control systems can damp the structural mode shapes and, in turn, significantly increase the chatter-free depth of cut. In order to reduce the commissioning effort, previous publications have introduced methodologies to automatically tune various control strategies for active damping. This paper presents a new automatic tuning approach for a robust model-based controller, which uses particle swarm optimization to find the best-performing control parameters. The proposed method was tested on both a 5-axis milling machine and a vertical lathe, together with an automatically tuned direct velocity feedback controller and an adaptive controller. The performance was evaluated by conducting extensive cutting tests under industrial operating conditions. All controllers and automatic tuning methodologies led to notable increase in chatter-free material removal rates, reduced vibration amplitudes, and improved surface roughness.