田延岭¹, 包亚洲¹, 王福军^1,2, 蔡坤海¹, 杨成娟¹, 张大卫¹
AuthorsHTML:田延岭¹, 包亚洲¹, 王福军^1,2, 蔡坤海¹, 杨成娟¹, 张大卫¹
AuthorsListE:Tian Yanling¹, Bao Yazhou¹, Wang Fujun^1,2, Cai Kunhai¹, Yang Chengjuan¹, Zhang Dawei¹
AuthorsHTMLE:Tian Yanling¹, Bao Yazhou¹, Wang Fujun^1,2, Cai Kunhai¹, Yang Chengjuan¹, Zhang Dawei¹
Unit:1. 天津大学机构理论与装备设计教育部重点实验室，天津 300350；2. 广东省精密装备与制造技术重点实验室，广州 510641
Unit_EngLish:1. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300350, China
2．Guangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology, Guangzhou 510641, China
Abstract_Chinese:设计了一种二自由度柔性微定位平台, 该平台主要由音圈电机和柔性铰链机构等组成．采用直角柔性铰链组成的双平行四杆机构对称安置, 以实现平台的大行程和运动解耦, 工作行程可达2 mm以上, 定位精度可达纳米级．设计空间支撑机构保证其承载能力．对微定位平台进行了结构设计和承载能力等特性分析．考虑到该定位平台动态行为的特点, 采用遗传算法优化的BP神经网络组合辨识方法对系统模型进行了辨识, 克服了神经网络对复杂系统动态行为辨识存在的缺陷．基于神经网络PID复合逆控制方法对微定位平台进行控制, 通过实验对辨识和控制方法进行了验证, 结果表明遗传算法优化的神经网络辨识方法与神经网络PID复合逆控制方法适用于该音圈电机驱动的柔性微定位平台系统的实际应用．
Abstract_English:A flexible micro positioning stage with 2-DOF driven by voice coil motors has been designed. The stage mainly contains voice coil motors and flexible hinge mechanism. A double parallel four-bar linkage composed of right angle flexible hinges was placed symmetrically in order to achieve a large motion stroke and motion decoupling. Its working stroke can reach more than 2 mm and positioning accuracy can reach the nanometer level. The space support mechanism was designed to ensure its carrying capacity. The structural design，bearing capacity and dynamic characteristics of the micro positioning stage were analyzed. Considering the characteristic of the dynamic behavior of the positioning stage，the BP neural network identification method optimized by genetic algorithm was used to identify the system model，which overcame the shortcomings of the neural network in dynamic behavior identification of complex system. Then the neural network PID compound inverse control method was applied to control the system. Experiments were carried out to verify the identification and control methods. The experimental results show that the neural network identification method optimized by genetic algorithm and the neural network PID compound inverse control method are suitable for the practical application of the flexible micro positioning system driven by voice coil motors.
Keyword_Chinese:微定位平台; 特性分析; 辨识; 控制
Keywords_English:micro positioning stage; characteristics analysis; identification; control

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