摘要
研究柔性关节空间机器人轨迹跟踪及关节柔性振动主动抑制问题.导出综合电机特性的动力学模型,且基于奇异摄动理论将其分解为快、慢变子系统.针对快变子系统,采用速度差值反馈控制;针对慢变子系统,提出一种基于径向基神经网络的全阶滑模控制.其中径向基神经网络用于逼近系统未知非线性项,全阶滑模兼备结构简单、鲁棒性强等优点的同时,还能克服抖振问题.系统数值仿真结果证明了所提方案的有效性.
The track tracking and active suppression of flexible vibration for the free-floating flexible joint space robot was studied.The dynamic model including motor dynamic was derived,and it was decomposed into fast and slow subsystems by using the singular perturbation theory.For fast subsystem,the velocity difference feedback control was adopted;and for slow subsystems,the full-order sliding mode control based on radial basis function(RBF)neural network was proposed.RBF neural network can approximate the nonlinear term of system,full-order sliding mode not only had the advantages of simple structure and strong robustness,but also could overcome the chattering problem.The numerical simulation results demonstrated the effectiveness of the proposed control strategy.
作者
朱安
陈力
ZHU An;CHEN Li(College of Mechanical Engineering and Automation,Fuzhou University,Fuzhou,Fujian 350108,China)
出处
《福州大学学报（自然科学版）》
CAS
北大核心
2019年第6期779-786,共8页
Journal of Fuzhou University(Natural Science Edition)
基金
国家自然科学基金资助项目(11372073)
福建省工业机器人基础部件技术重大研发平台资助项目(2014H21010011)
关键词
柔性关节空间机器人
柔性振动
主动抑制
电机特性
径向基神经网络
全阶滑模
flexible joint space robot
flexible vibration
active suppression
motor dynamic
radial basis function neural network
full-order sliding mode
