Adaptive Neural Network Control for Piezoelectric Hysteresis Compensation in A Positioning System

Piezoelectric (PZT) actuators are popularly applied as actuators in micro-positioning systems due to its characteristic of infinitely small displacement resolution. Piezoelectricity material has nonlinear hysteresis phenomena. Owing to its nonlinear hysteresis effect, the tracking control accuracy of the precision positioning system is difficultly achieved. Hence, it is desirable to take hysteresis effect into consideration for improving the control performance. In this paper, a trajectory tracking controllers composed of adaptive neural network and PI controller is presented for a nano-positioner driven by a piezoactuator to realize the control performance that the displacement of a nano-positioner driven by a piezo-actuator can follow accurately the reference input signal and the transient response of the system can be improved. In this paper, some computer simulations are made to show that the system output can track the reference input exactly and the system transient response can be improved