Adaptive Identification and Control of Hysteresis in Piezoelectric Actuators

Abstract

Smart actuators, such as piezoceramic actuators, magnetostrictive actuators, and shape memory alloy actuators are widely used in applications of micrositioning and vibration control. Piezoelectric (PZT) actuators having the characteristic of infinitely small displacement resolution are popularly applied as actuators in precision positioning systems. However, the tracking control accuracy of the precision positioning systems is difficultly achieved because of its nonlinear hysteresis effect. Hence, it is important to take hysteresis effect into consideration for improving the trajectory tracking performance. In this paper, in order to capture the hysteresis nonlinearity in the PZT actuators, the Hammerstein model is put to use. The fuzzy control algorithm is used to identify the weighing values. The adaptive inverse controller based on adaptive fuzzy inference is used to track the PZT actuator. We firstly identify the weighting values of the Hammerstein model in situ using the multi-mode fuzzy control algorithm based on the error between reference displacement and actual displacement of the actuator, and then calculate the weighting values and threshold values of the Hammerstein model. Finally, we obtain the feed-forward input voltage. The stability of the controller in the presence of the estimated state is demonstrated. The experimental results show the performance is effectively improved under the intelligent control method.