Application of the Taguchi-genetic method to design an optimal grey-fuzzy controller of a constant turning force system

Abstract

A grey-fuzzy control scheme is proposed in this paper to control a constant cutting force turning process under various cutting conditions. The grey-fuzzy control scheme consists of two parts: a grey predictor and the fuzzy logic controller. When the grey-fuzzy control scheme is used to design the constant turning force system, it is necessary to adjust the control parameters of both the grey predictor and the fuzzy controller (i.e., the sample size and grey constants of the grey predictor, and the scaling factors of the fuzzy controller) for ensuring stability and obtaining optimal control performances. Therefore, in order to search for the optimal control parameters by way of systematic reasoning instead of the time-consuming trial-and-error procedure, the Taguchi-genetic method is applied in this paper to search for the optimal control parameters of both the grey predictor and the fuzzy controller such that the grey-fuzzy controller is an optimal controller. Computer simulations are performed to verify the effectiveness of the above optimal grey-fuzzy control scheme designed by the Taguchi-genetic method. It is shown that satisfactory performance is achieved by the designed optimal grey-fuzzy control scheme.