Modeling for Giant Magnetostrictive Actuators with Rate-Dependent Hysteresis based on Hammerstein-like System by Using LS-SVM

作     者：Ping Liu 1 , Zhen Zhang 1 , Jianqin Mao 1 , Kemin Zhou 2 , 1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics & Astronautics, Beijing 1001912. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031 

会议名称：《第24届中国控制与决策会议》

会议日期：2012年

学科分类：08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 

基　　金：supported by National Nature Science Foundation of China (91016006) 

关 键 词：GMA LS-SVM Hammerstein-like Hysteresis PSO Rate-dependent 

摘      要：The rate-dependent hysteresis in giant magnetostrictive materials is a major impediment to the application of such material in actuators . In this paper, a Hammerstein-like model based on Least Square Support Vector Machines （LS-SVM） is proposed to model the rate-dependent hysteresis system. We show that it is possible to construct a unique dynamic model in a given frequency range for a rate-dependent hysteresis system using the sinusoidal scanning signals as the training set of signals for the linear dynamic subsystem of the Hammerstein-like model, which guarantees an outstanding generalization ability of frequency. The LS-SVM parameters influencing the model accuracy are determined through the intelligent particle swarm optimization （PSO） and the dimension of input data is also discussed. Simulations on a giant magnetostrictive actuator （GMA） verify both the effectiveness and practicality of the proposed modeling method.