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

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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… Click to show full abstract

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.

Keywords: evolution algorithm; magnetostrictive actuator; giant magnetostrictive; differential evolution; simulated annealing

Journal Title: AIP Advances
Year Published: 2018

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