天文望远镜子镜超磁致伸缩驱动器驱动模型及参数识别
Modeling and Parameter Identification for Giant Magnetostrictive Actuators Applied in Driving Segmented Mirrors
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摘要: 采用超磁致伸缩驱动器(GMA, Giant Magnetostrictive Actuator)驱动拼接镜面天文望远镜子镜,并建立GMA精密位移驱动准确模型。针对传统遗传算法在辨识GMA位移模型参数时容易过早收敛到次优解的问题,提出了基于分层遗传算法(HGA, Hierarchical Genetic Algorithm)的参数识别方法,其结果在改善驱动位移模拟准确性和提高求解初期种群多样性,相对于其他算法都有较大程度的提高。研究通过与实验结果对比验证了所提出参数辨识方法和建立模型的有效性,位移预测值和实验值的平均偏离值不超过满行程的1.3%。研究还就驱动磁场强度幅值和预应力等因素对滞回、损耗、饱和磁化强度、饱和磁致伸缩量等模型参数的影响进行了分析。Abstract: The research in this paper focuses on establishing an accurate displacement model for giant magnetostrictive actuators (GMA)that may be istalled in a very large telescope to drive its segmented mirrors. A hierarchical genetic algorithm (HGA)is proposed and employed to identify the parameters for effectively deploying the GMA model. In practice, the HGA is proved to be able to avoid the problem of conventional genetic algorithms that the algorithms converge to suboptimal solutions. The HGA allows more initial population diversity in calculation and practically improves significantly the accuracy in predicting the actuator displacement. The deviations between experimental data and predicted values are less than 1.3% across the entire displacement range. Comparisons between the predicted values and experimental results imply that the established model precisely describes the hysteretic behavior and displacement characterization of GMA. The paper also analyzes effects on the key parameters in the model (such as hysteresis, loss, saturation magnetization, and saturation magnetostriction)from the applied magnetic field strength and the prestress level.