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.
A new optimal robust adaptive fuzzy controller for a class of non-linear under-actuated systems
