Identification and Compensation of Piezoelectric Hysteresis Without Modeling Hysteresis Inverse

Abstract

This paper presents a new approach for hysteresis identification and compensation of piezoelectric actuators by resorting to an intelligent hysteresis model. In particular, a least squares support vector machine (LSSVM)-based hysteresis model is developed and used for both purposes of hysteresis identification and hysteresis compensation. By this way, the hysteresis inverse is not needed in the feedforward hysteresis compensator since the hysteresis model is directly used. To establish the LSSVM model, the problem of how to select input variables to convert the multivalued mapping into a single-valued one is addressed. The effectiveness of the presented idea is validated by a series of experimental studies on a piezoactuated system. Results show that the proposed approach is superior to the Bouc–Wen-model-based one in terms of both hysteresis modeling and compensation. The reported method is more computational effective than existing model-based hysteresis compensation approaches, and it is extensible to other smart actuator systems as well.