Learning control of robot manipulators in the presence of additive disturbances


Abstract: In this paper, a learning controller for robot manipulators is developed. The controller is proven to yield in a semi-global asymptotic result in the presence of additive input and output disturbances. Lyapunov-based techniques are used to guarantee that the tracking error is asymptotically driven to zero. Numerical simulation results are presented to demonstrate the viability of the proposed learning controller.

Keywords: Learning control, disturbance rejection, Lyapunov--based methods

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