A new design of adaptive fuzzy hybrid force/position controller for robot manipulators

The major problems of hybrid force/position control arise from uncertainty of the robot manipulators and unknown parameters of the task environment. In this paper, a new design method of the hybrid force/position control of the robot manipulators is proposed to solve these problems. The control objective is to track the desired force and position trajectories simultaneously regardless of the unknown parameters of the task environment and the existence of the manipulator dynamics, represented as a fuzzy rule-base. The algorithm embedded in the proposed architecture can automatically update the fuzzy rules and, consequently, guarantee the global stability and drive the tracking errors to a neighborhood of zero. The present work is applied to the control of a five degree-of-freedom (DOF) articulated robot manipulator. Simulation results show that the proposed control architecture is featured in fast convergence.