Optimal predicted fuzzy controller of a constant turning force system with fixed metal removal rate

The grey-fuzzy control scheme, which is a predictive fuzzy control scheme, is proposed in this paper to control the constant turning force process with a fixed metal removal rate under various cutting conditions. The grey-fuzzy control scheme consists of two parts: the grey predictor and the fuzzy logic controller. When the grey-fuzzy control scheme is used to design the constant turning force operation with a fixed metal removal rate, 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 performance. 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 has been achieved by this designed optimal grey-fuzzy control scheme.