Robust gain scheduled position/force hybrid control for a robot interacting with uncertain flexible environment

Abstract

This paper studies on how to specify a position/force hybrid control for a robot manipulator that has model uncertainties to interact with its uncertain flexible environment. The distributed parameter dynamics of the environment as seen from the robot's end-effector is formulated as an uncertain linear parameter-varying system (ULPV), varying with respect to the robot's contact position. The robot's dynamics is decomposed into position control loop and force control loop in task space using nonlinear feedback compensation. Based on the quadratic stability theory, gain scheduled control is developed for controlling the robot's uncertain force control loop. It is found that, although after the decomposition, the robot's position control loop is not directly influenced by the contact force, the robot's moving velocity influences the solution of the force control loop's Riccati equation. Hence the position control loop should be designed with respect to the force control loop.