Neural Fuzzy Prediction Control of an Industrial Grinding Process

In this paper, the neural network and fuzzy logic are introduced to the grinding process to prediction and control workpiece size. Dynamic Elman neural network is used in the prediction model. We modified the hidden layer structure, and the first and the second derivative of the actual amount removed from the workpiece are added into the network input, which can greatly improve the prediction accuracy. A fuzzy control model with flexible factor is used to control workpiece size. Simulation and experiment verify that the developed prediction control model is feasible and has high prediction and control precision.