Learning and adaptive controls for coordination of multiple manipulators without knowing physical parameters of an object

Learning control and model-based adaptive control schemes are proposed for coordinated control of multiple manipulators when physical parameters such as inertia moments and position of the mass center of a target object are unknown. The proposed schemes are constructed on the equation of motion of the coordinated multiple manipulators, which is derived in terms of joint angle coordinates of manipulators and includes the dynamics of the target object. Since this equation does not explicitly include the position of the mass center of the object, the proposed schemes can achieve exact tracking of given joint angle trajectories and given trajectories of “internal force” without using physical parameters of the manipulators and the object. The effectiveness of the proposed schemes is illustrated by the numerical simulation results on a model of two 3-DOF manipulators holding a single object