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

Abstract

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.

Optimal constrained integral sliding mode control design for fuzzy-based nonlinear systems

“…Some of other robust control methods for nonlinear systems based on the TS fuzzy system have been studied in recent years (Du et al, 2021; Mohammadi Moghadam et al, 2022; Rajendran et al, 2020; Silva et al, 2022). A robust fuzzy controller has been developed in Hosseinalizadeh et al (2019) to control the voltage and the frequency of an islanded AC microgrid based on the L 2 gain approach.…”

Research on the formation mechanism of surface morphology in three-excitation ultrasonic spatial vibration-assisted turning

“…Due to the initial stress, the nonlinearity of the material, and the large deformation, the non-resonant 3D-EVT system generally has nonlinearity and uncertainty. In order to solve this problem, Lin et al [40][41] combined the non-resonant 3D-EVT system with robust adaptive fuzzy control technology to improve the stability of the system. Compared with the ordinary non-resonant 3D-EVT system, the surface roughness obtained by the improved 3D-USVT system is reduced by 20% ~32%.…”