Modeling for Giant Magnetostrictive Actuators with Rate-Dependent Hysteresis based on Hammerstein-like System by Using LS-SVM
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.
GMA LS-SVM Hammerstein-like Hysteresis PSO Rate-dependent
Ping Liu Zhen Zhang Jianqin Mao Kemin Zhou
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics & Astrona School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
2597-2602
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）