机器人实现未知参数下的曲面跟踪和恒力控制的研究
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摘要
随着"工业4.0"的到来,机器人与环境接触的任务需求越来越多,比如打磨、抛光和装配。机器人与环境接触的力控制成为了一个热门的需求。传统的基于位置控制的阻抗控制算法实现机器人与环境接触的力控制,一般都需要准确地知道环境的刚度,并且传统的阻抗控制算法并没有使用力闭环检测环节。因此,传统的阻抗控制方法实现接触力的控制其精度并不高,很难满足现代化生产的要求。针对这个问题,提出了基于模糊PI的力闭环阻抗控制方法,该方法在传统的阻抗控制模型上增加了力闭环反馈环节,能实时采集接触力的信息,实现对接触力的精确控制,并且不需要知道环境的刚度,易于实现。
With the advent of industry 4. 0,tasks of robots in contact with the environment have more and more demands,such as grinding,polishing and assembly,robot and environmental contact force control has become a popular demand. Robot uses the traditional position control based impedance control algorithm to achieve constant contact with the environment control,generally need to accurately know the stiffness of the environment. And the traditional impedance control algorithm does not require the use of force sensors which lacks of force closed loop detection. Therefore,only the use of traditional impedance control method to achieve the control of contact force accuracy is not high. Aiming at this problem,this paper presents a fuzzy PI-based force closed-loop impedance control method,which achieves precise control of the contact force through the force closed-loop feedback link,and does not need to know the stiffness of the environment and is easy to implement.
With the advent of industry 4. 0,tasks of robots in contact with the environment have more and more demands,such as grinding,polishing and assembly,robot and environmental contact force control has become a popular demand. Robot uses the traditional position control based impedance control algorithm to achieve constant contact with the environment control,generally need to accurately know the stiffness of the environment. And the traditional impedance control algorithm does not require the use of force sensors which lacks of force closed loop detection. Therefore,only the use of traditional impedance control method to achieve the control of contact force accuracy is not high. Aiming at this problem,this paper presents a fuzzy PI-based force closed-loop impedance control method,which achieves precise control of the contact force through the force closed-loop feedback link,and does not need to know the stiffness of the environment and is easy to implement.
引文
[1]李正义,唐小琦,熊烁,等.沿任意倾斜面的机器人力/位置控制方法研究[J].中国机械工程,2012,23(3):304-309.
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[6]Jung S,Hsia TC.Neural network impedance force control of robot manipulators[J].IEEE Trans.Ind.Electron.,1998,45:451-461.
[7]Jung S,Hsia TC.Robust neural force control scheme under uncertainties in robot dynamics and unknown environment[J].IEEE Trans.Ind.Electron,2000,47(2):403-412.
[8]Jung S,Yim S B,Hsia T C.Experimental studies of neural network impedance force control for robot manipulators[J].IEEE Conf.Robotics Automation,2001,4:3453-3458
[2]Seraji H,Colbaugh R.Force tracking in impedance control[J].IEEEInt.Conf.Robotics Automation,2002,16(1):499-506.
[3]Seraji H.Adaptive admittance control:An approach to explicit force control in compliant motion[J].IEEE Int.Conf.Robotics Automation,2002,4:2705-2712
[4]Colbaugh R,Engelmann A.Adaptive compliant motion of manipulators:Theory and experiments[J].IEEE Int.Conf.Robotics Automation,1994,14(7):2628-2635.
[5]Pliego-Jiménez J,Arteaga-Pérez M A.Adaptive position/force control for robot manipulators in contact with a rigid surface with uncertain parameters[J].European Journal of Control,2015,22:1-12.
[6]Jung S,Hsia TC.Neural network impedance force control of robot manipulators[J].IEEE Trans.Ind.Electron.,1998,45:451-461.
[7]Jung S,Hsia TC.Robust neural force control scheme under uncertainties in robot dynamics and unknown environment[J].IEEE Trans.Ind.Electron,2000,47(2):403-412.
[8]Jung S,Yim S B,Hsia T C.Experimental studies of neural network impedance force control for robot manipulators[J].IEEE Conf.Robotics Automation,2001,4:3453-3458