Stable fuzzy self-tuning computed-torque control of robot manipulators

Computed-torque control is a well known motion control strategy for manipulators which ensures global asymptotic stability for fixed symmetric positive definite (proportional and derivative) gain matrices. We show that the global asymptotic stability attribute also holds for a class of gain matrices depending on the manipulators state. This feature increases the potential of the computed-torque scheme to handle practical constraints in actual robots such as presence of friction in the joints and actuators with limited torque capabilities. We illustrate this potential by means of a fuzzy self-tuning algorithm to select the proportional and derivative gains according to the actual tracking position error. Experiments on a two degrees of freedom robot arm shown the usefulness of the proposed approach