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. Elliptical vibration cutting (EVC), as a precision machiningtechnology, is used in many applications. In precision machining, controlaccuracy plays an essential role in improving the machinability ofdifficult-to-machine materials. To improve the control accuracy, dynamicand static characteristics of the system need to be tuned to obtain theoptimal 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 throughsimulation. The optimal solution of the controller parameters is thenapplied to a 3D EVC system model for simulation and closed-loop testingexperiments. The results indicate that a good agreement between the idealcurve and the tracking signal curve verifies the optimality of thecontroller parameters. Finally, under certain cutting conditions, theworkpieces of three different materials are cut with two different cuttingmethods. The study revealed that the surface roughness value is reduced by20 %–32 %, which further verifies the effectiveness of the optimalcontroller's parameters.

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