摘要
冗余驱动并联机构驱动数目大于自由度数目,其各驱动关节间需要具有更高的驱动协调性。为了解决冗余驱动并联机构的驱动协调问题,本文提出了一种基于模型的驱动力同步协调控制方法。以冗余驱动并联机构6PUS+UPU为研究对象,在力位混合驱动的基础上,提出了一种驱动力同步协调控制策略;结合神经网络设计了驱动力同步控制器,并基于机构动力学模型设计了神经网络自学习算法。模型仿真与样机实验分别验证了本文方法的有效性。
Redundantly actuated parallel manipulator demands higher actuation coordination than the non-redundantly actuated one,thanks to its degree of actuation exceeding its degree of freedom. To improve the actuation coordination of redundantly actuated parallel manipulator,a novel model-based driving force synchronous control method with neural network was proposed. With 6 PUS ＋ UPU parallel manipulator as object,dynamic model was derived based on virtual work principle. To improve the actuation coordination of redundantly actuated parallel manipulator,a novel driving force synchronous control method was proposed on basis of force-position hybrid actuation. The synchronous control method was based on the driving force error of actuated joints and driving force adjustment was calculated by the synchronous controller. The synchronous controller was designed with neural network. What＇s more,the learning law of neural network controller was derived with manipulator＇s dynamic model to improve the learning efficiency. Model simulation and prototype experiment were carried out,and a performance comparison analysis with traditional force-position hybrid actuation method was made to verify the proposed control method. Comparison analysis revealed that,comparing with the traditional force-position hybrid actuation method,driving force synchronous control with neural network proposed could effectively improve the actuation coordination of redundantly actuated parallel manipulator. The results revealed that the synchronous control method reduced the driving force errors of whole manipulator by properly magnifying the control error of force actuated joint.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2018年第2期367-375,共9页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金项目(51675458
51675459)
河北省自然科学基金项目(E2017203387)
河北省高等学校青年拔尖人才计划项目(BJ2017060)
关键词
并联机构
冗余驱动
驱动力同步协调
力位混合驱动
动力学模型
神经网络
parallel manipulator
redundantly actuated
driving force synchronous control
forceposition hybrid control
dynamic model
neural network
作者简介
刘晓飞（1986-），男，博士生，主要从事并联机构动力学与控制研究，E-mail：xfliu@stumail．ysu．edu．cn;通信作者：赵永生（1962-），男，教授，博士生导师，主要从事机器人、多维力传感器以及先进制造技术研究，E-mail：yszhao@ysu．edu．cn
