超磁致伸缩驱动器输出位移模型参数的辨识方法

Identification Method for Output Displacement Model Parameters of Giant Magnetostrictive Actuator

为了提高超磁致伸缩驱动器的控制精度和响应速度,需要快速精确获取其磁滞非线性模型中的未知参数。在介绍超磁致伸缩驱动器工作原理的基础上,基于Jiles-Atherton模型建立了GMA的磁滞非线性模型,并提出一种改进型粒子群算法对其模型参数进行辨识,最后搭建仿真和实验平台进行验证。结果表明:该改进型粒子群算法辨识GMA输出位移模型参数有效性高,参数辨识代码运行时间缩短至210s,适应度函数值最小达到0. 165 7,由此建立的磁滞非线性模型的计算精度可精确到0. 001μm,且通过多次比较发现该位移输出模型重复性较高,研究结果为后续进行GMA输出位移的误差补偿控制提供理论依据。

In order to improve the control accuracy and response speed of giant magnetostrictive actuator,it is necessary to obtain the parameters of its hysteresis nonlinear model quickly and accurately.On the basis of the introduction of the working principle of the giant magnetostrictive actuator,this paper adopted the Jiles-Atherton model to establish the hysteresis nonlinear model of GMA,and proposed an improved particle swarm optimization algorithm to identify the model parameters,and finally built the simulation and experimental platform to verify it.The results show that the improved particle swarm optimization can identify the GMA output displacement model with high accuracy,the precision of the hysteresis nonlinear model can be up to 0.001μm,with the minimum fitness function value being 0.165 7,and the running time of the parameter identification code was shortened to 210s.The GMA displacement output model established by the identification parameters can be used in the prediction of the actual output displacement.