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Prandtl-Ishlinskii Model Identification Strategy Based on An Improved Particle Swarm Optimization Algorithm

Prandtl-Ishlinskii (PI) model is used to describe the hysteresis nonlinear characteristics of piezoelectric actuator. It has many parameters which are difficult to identify. In order to overcome the drawback, an adaptive particle swarm optimization (PSO) algorithm is proposed in this paper. The algorithm combines the adaptive adjustment of the weighting factor and the non-linear change of the learning factor. As a result the algorithm has a good global searching ability in the early stage and a fast convergence speed. After the algorithm is iterated to the later stage, the local searching ability is enhanced and the model accuracy is improved. Simulation results show that the proposed adaptive PSO algorithm has faster convergence speed and higher accuracy compared with the PSO Scheme.