Feedback-error Learning for Explicit Force Control of a Robot Manipulator Interacting with Unknown Dynamic Environment

Abstract

Force control of a robot manipulator is important for the robot to perform physical interaction with its manipulated objects as well as its environment. Usually, the environmental dynamics is unknown and during interactions the environmental dynamics will influence the robot’s control loop. In this research, based on the fact that the transfer function from the robot’s control torque to the environmental reaction force is biproper, a novel 2 degree of freedom adaptive control approach is presented and is applied for the explicit force control of the robot manipulator. In this approach, both force feedback and feedforward controllers are involved in the robot’s control system, the feedback control is set as constant while the feedforward controller is adjusted adaptively online to approach the inverse of the force control transfer function. Using this approach, exact force response without any loop delay can be realized. Computer simulations show the effectiveness of this control approach.