Parameter tuning of robust adaptive fuzzy controller for 3D elliptical vibration-assisted cutting

Abstract

Elliptical vibration cutting (EVC), as a precision machining technology, is used in many applications. In precision machining, control accuracy plays an essential role in improving the machinability of difficult-to-machine materials. To improve the control accuracy, dynamic and static characteristics of the system need to be tuned to obtain the optimal parameters. In this paper, we use a glowworm algorithm with an improved adaptive step size to tune the parameters of a robust adaptive fuzzy controller. We then obtain the optimal controller parameters through simulation. The optimal solution of the controller parameters is then applied to a 3D EVC system model for simulation and closed-loop testing experiments. The results indicate that a good agreement between the ideal curve and the tracking signal curve verifies the optimality of the controller parameters. Finally, under certain cutting conditions, the workpieces of three different materials are cut with two different cutting methods. The study revealed that the surface roughness value is reduced by 20 %–32 %, which further verifies the effectiveness of the optimal controller's parameters.