Neuron net control and its application in precision feed mechanism of machine tools driven by PZT

In this paper a novel monolayer neural net model and learning algorithm are proposed to control a precision feed mechanism driven by piezoelectric ceramics (PZT) of machine tools. Experiment shows that the neural net control enables the cutter to trace the teaching signals rapidly and accurately, although the PZT cutter feed mechanism has characteristics of nonlinearity and hysteresis.