Dynamic modeling of hysteresis nonlinearity based on improved Particle Swarm Optimization algorithm

Hysteresis which is inherent in smart sensors or actuators may severely deteriorate system performance such as giving rise to undesirable inaccuracies or oscillations, even leading to instability. Therefore, it is necessary to find a model describing the behavior of hysteresis. In this method, an improved hysteretic operator is proposed to describe the change tendency and extract the dynamic property of rate-dependent hysteresis. Then a dynamic hysteresis model is established with introduction of such hysteresis operator combined with a linear system. An improved PSO (Particle Swarm Optimization) algorithm is used for identification of parameters. The established model has a brief structure and few parameters. Finally, the method of modeling hysteresis nonlinearity is applied in piezoelectric actuators and compared with PI model. The results indicate that this model is able to accurately describe the characteristics of hysteresis nonlinearity in the actual system.