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Iterative learning control for robot manipulators

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In this paper, we present a time-domain iterative learning control scheme for the trajectory tracking problem of rigid robot manipulators that perform repeated tasks. The proposed control scheme comprises a computed torque control designed exploiting the approximated linear model of a manipulator and a learning law to compensate effects of nonlinear terms, that are ignored in obtaining the linear model, and the external disturbance. We show that the iterative learning controller is capable of effectively canceling the disturbances caused by nonlinear terms and other disturbance. The asymptotic stability of the closed-loop system is guaranteed, and the conditions of this stability are given. Simulation results on PUMA 560 robot show clearly efficiency of the proposed scheme.
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Bibliogr. 13 poz., rys.
  • Laboratoire de Commande des Processus, Ecole Nationale Polytechinque, Elharrach, Algiers, Algeria,
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