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Parameter identification based on modified simulated annealing differential evolution algorithm for giant magnetostrictive actuator

机译:基于改进的模拟退火差分进化算法的巨磁致伸缩执行器参数辨识

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There is a serious nonlinear relationship between input and output in the giant magnetostrictive actuator (GMA) and how to establish mathematical model and identify its parameters is very important to study characteristics and improve control accuracy. The current-displacement model is firstly built based on Jiles-Atherton (J-A) model theory, Ampere loop theorem and stress-magnetism coupling model. And then laws between unknown parameters and hysteresis loops are studied to determine the data-taking scope. The modified simulated annealing differential evolution algorithm (MSADEA) is proposed by taking full advantage of differential evolution algorithm’s fast convergence and simulated annealing algorithm’s jumping property to enhance the convergence speed and performance. Simulation and experiment results shows that this algorithm is not only simple and efficient, but also has fast convergence speed and high identification accuracy.
机译:巨磁致伸缩执行器(GMA)的输入和输出之间存在严重的非线性关系,如何建立数学模型并确定其参数对于研究特性和提高控制精度非常重要。首先基于Jiles-Atherton(J-A)模型理论,Ampere回路定理和应力-磁力耦合模型建立了电流-位移模型。然后研究未知参数与磁滞回线之间的规律,以确定数据采集范围。通过充分利用差分进化算法的快速收敛性和模拟退火算法的跳跃特性,提出了改进的模拟退火差分进化算法(MSADEA),以提高收敛速度和性能。仿真和实验结果表明,该算法不仅简单高效,而且收敛速度快,识别精度高。

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