This paper presents the development of a resolved motion adaptive control which adopts the ideas of “resolved motion rate control” [8] and “resolved motion acceleration control” [10] to control a manipulator in Cartesian coordinates for various loading conditions. The proposed adaptive control is performed at the hand level and is based on the linearized perturbation system along a desired hand trajectory. The controlled system is characterized by feedforward and feedback components which can be computed separately and simultaneously. The feedforward component resolves the specified positions, velocities, and accelerations of the hand into a set of values of joint positions, velocities, and accelerations from which the nominal joint torques are computed using the Newton-Euler equations of motion to compensate all the interaction forces among the various joints. The feedback component consisting of recursive least square identification scheme and an optimal adaptive self-tuning controller for the linearized system computes the perturbation torques which reduce the manipulator hand position and velocity errors along the nominal hand trajectory. The feasibility of implementing the proposed adaptive control using present day low-cost microprocessors is explored.

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