Stiffness adjustment is an important feature of human arm control.The adaptive variable impedance control can adapt to the robotic stiffness,but may result in a large overshoot.In this paper,nonlinear impedance contro...Stiffness adjustment is an important feature of human arm control.The adaptive variable impedance control can adapt to the robotic stiffness,but may result in a large overshoot.In this paper,nonlinear impedance control is proposed for collaborative robotic grinding,where nonlinear force feedback is designed to compensate for the nonlinear stiffness of the environment.Thus,the interaction system can be linearization to ensure the system stability.Moreover,a target trajectory adaptation strategy is studied to ensure the force tracking requirement.Then,switching law between trajectory tracking and force tracking is proposed when the robot performs a complex grinding task.The stability of the switch control as well as the trajectory adaptation law is proved.Experiments are conducted in a robotic grinding test rig,where the robot is used to grind a turbine blade.Experimental results show that the nonlinear impedance control can obtain stable grinding force,and have better grinding quality than the linear impedance control.展开更多
基金supported by the National Key Research and Development Program of China (Grant No.2022YFB4702200)the National Natural Science Foundation of China (Grant Nos.52275020,62293514)。
文摘Stiffness adjustment is an important feature of human arm control.The adaptive variable impedance control can adapt to the robotic stiffness,but may result in a large overshoot.In this paper,nonlinear impedance control is proposed for collaborative robotic grinding,where nonlinear force feedback is designed to compensate for the nonlinear stiffness of the environment.Thus,the interaction system can be linearization to ensure the system stability.Moreover,a target trajectory adaptation strategy is studied to ensure the force tracking requirement.Then,switching law between trajectory tracking and force tracking is proposed when the robot performs a complex grinding task.The stability of the switch control as well as the trajectory adaptation law is proved.Experiments are conducted in a robotic grinding test rig,where the robot is used to grind a turbine blade.Experimental results show that the nonlinear impedance control can obtain stable grinding force,and have better grinding quality than the linear impedance control.
