空间站载荷转移机构机器人的力加载控制方法
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摘要
针对机器人在空间站载荷转移机构力加载过程中,由于展开完成后的载荷转移机构在力的方向上发生变形,导致机器人力控制系统难以保持稳定、加载精度不足或调节时间过长的问题,提出了自适应调整导纳控制器参数的策略.首先,根据导纳控制理论建立力与位移的关系,初步提出了基于直角坐标系的力跟随/力加载控制器;然后,根据加载实验数据,采用最小二乘法对载荷转移机构模型进行参数辨识,建立机器人特定工作空间的力与位置关系;最后,通过自适应调整导纳控制器参数使机器人动力学模型与载荷转移机构的动力学模型近似匹配,实现机器人对展开完成后的载荷转移机构末端的空间力实时加载.实验得出机器人对载荷转移机构位置跟随偏差不超过0.1 mm,加载力误差不超过1%.仿真结果表明,该机器人满足精度要求,为载荷转移机构提供了较为真实的等效空间载荷.
When the robot loading force on the load transfer mechanism of space station, there exist some problems caused by the deformation of the load transfer mechanism along the force direction after spreading, such as unstable robot force control system, insufficient load accuracy, and long settling time. To solve these problems, a strategy for adjusting the admittance controller parameters adaptively is proposed. Firstly, the relationship between force and position is established according to the admittance control theory. And a force tracking/force loading controller based on the rectangular coordinate system is initially designed. Then, the parameters of the load transfer mechanism model are identified based on the loading experiment data by the least square method, and the relationship between force and position of robot in specific workspace is established. Finally, the parameters of the admittance controller are adaptively adjusted to make the robot dynamics model approximately match with the dynamic model of the load transfer mechanism. The real-time spatial loading force imposed by the robot on the end of the load transfer mechanism after spreading is realized. The experiment shows that the tracking error of the robot relative to the load transfer mechanism is less than 0.1 mm, and the loading force error is less than 1%. The simulation results show that the robot meets the precision requirement and provides a real equivalent space load for the load transfer mechanism.
When the robot loading force on the load transfer mechanism of space station, there exist some problems caused by the deformation of the load transfer mechanism along the force direction after spreading, such as unstable robot force control system, insufficient load accuracy, and long settling time. To solve these problems, a strategy for adjusting the admittance controller parameters adaptively is proposed. Firstly, the relationship between force and position is established according to the admittance control theory. And a force tracking/force loading controller based on the rectangular coordinate system is initially designed. Then, the parameters of the load transfer mechanism model are identified based on the loading experiment data by the least square method, and the relationship between force and position of robot in specific workspace is established. Finally, the parameters of the admittance controller are adaptively adjusted to make the robot dynamics model approximately match with the dynamic model of the load transfer mechanism. The real-time spatial loading force imposed by the robot on the end of the load transfer mechanism after spreading is realized. The experiment shows that the tracking error of the robot relative to the load transfer mechanism is less than 0.1 mm, and the loading force error is less than 1%. The simulation results show that the robot meets the precision requirement and provides a real equivalent space load for the load transfer mechanism.
引文
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[2]Ayas M S,Altas I H.Fuzzy logic based adaptive admittance control of a redundantly actuated ankle rehabilitation robot[J].Control Engineering Practice,2017,25(1):44-54.
[3]陈贵亮,曹伟涛,杨冬,等.基于阻抗控制的幕墙安装机器人柔顺操作研究[J].工程设计学报,2017,24(1):100-107.Chen G L,Cao W T,Yang D,et al.Compliant operation research for slabstone-installing robot based on impedance control[J].Chinese Journal of Engineering Design,2017,24(1):100-107.
[4]He W,Dong Y T.Adaptive fuzzy neural network control for a constrained robot using impedance learning[J].IEEE Transactions on Neural Networks and Learning Systems,2017,doi:10.1109/TNNLS.2017.2665581.
[5]He W,Dong Y T,Sun C Y.Adaptive neural impedance control of a robotic manipulator with input saturation[J].IEEE Transactions on Systems,Man,and Cybernetics Systems,2016,46(3):334-344.
[6]Ranatunga I,Lewis F L,Popa D O,et al.Adaptive admittance control for human-robot interaction using model reference design and adaptive inverse filtering[J].IEEE Transactions on Control Systems Technology,2017,25(1):278-285.
[7]刘强,扈宏杰,刘金琨.高精度飞行仿真转台的鲁棒自适应控制[J].系统工程与电子技术,2001,23(10):35-38.Liu Q,Hu H J,Liu J K.Robust adaptive control of high precision flight simulator[J].Systems Engineering and Electronics,2001,23(10):35-38.
[8]Alqaudi B,Modares H,Ranatunga I.Model reference adaptive impedance control for physical human-robot interaction[J].Control Theory and Technology,2016,14(1):68-82.
[9]Landi C T,Ferraguti F,Sabattini L,et al.Admittance control parameter adaptation for physical human-robot interaction[C]//IEEE International Conference on Robotics and Automation.Piscataway,USA:IEEE,2017:2911-2916.
[10]Dimeas F,Aspragathos N.Online stability in human-robot cooperation with admittance control[J].IEEE Transactions on Haptics,2016,9(2):267-278.
[11]Jung S,Hsia T C,Bonitz R G.Force tracking impedance control of robot manipulators under unknown environment[J].IEEETransactions on Control Systems Technology,2004,12(3):474-483.
[12]Lee K,Buss M.Force tracking impedance control with variable target stiffness[J].IFAC Proceedings Volumes,2008,41(2):6751-6756.
[13]崔亮.机器人柔顺控制算法研究[D].哈尔滨:哈尔滨工程大学,2013.Cui L.The research of compliance control algorithms on robot[D].Harbin:Harbin Engineering University,2013.