Adaptive Hybrid Control for a Robot Manipulator Interacting with Uncertain Flexible Environments

Abstract

This paper presents an adaptive position/force hybrid control approach for a robot manipulator to interact with its uncertain flexible environments. Because of its flexibility, the environment dynamics influences the robot's control system, and since it is a distributed parameter system, the environment dynamics as seen from the robot changes when the robot moves. The problem becomes further complicated such that it is difficult to decompose the robot's position and force control loops. In this paper, the environment's distributed parameter dynamics is approximated into a lumped "position state-varying" model. The robot's control space is decomposed into a position control subspace and an environment torque control subspace. Optimal state feedback is designed for the position control loop, and model-reference simple adaptive control is applied to the force control loop. Experiments show the effectiveness of this control approach.