Particle swarm optimization based modeling and compensation of hysteresis of PZT micro-actuator used in high precision dual-stage servo system

Piezoelectric micro-actuator made from PZT (Lead-Zirconium-Titanium) has been a popular choice as the secondary actuator of a dual-stage actuator system. However, the advantage gained by the precision of secondary actuator is somewhat lost by the inherent hysteresis nonlinearity of PZT actuator, if not compensated. This paper proposes a new rigorous technique for modeling and compensation of the hysteresis of PZT actuator used in dual-stage actuator system, which is established by artificial intelligence based heuristic optimization technique based on particle swarm optimization. In this paper, first the model parameters of Generalized Prandtl-Ishlinskii (GPI) model are identified off-line by PSO technique and corresponding inverse GPI is obtained as the hysteresis compensator. Then in case of parameter uncertainty, PSO based online tuning method is employed to adaptively adjust the parameters of inverse GPI model. For the linear controller of dual-stage, a simple design approach is followed. Simulation results show that the proposed technique can be efficiently used for the identification of hysteresis of PZT micro-actuator and the adaptive tuning the parameters of the effectiveness of the design.