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In this paper an adaptive multi-priority nonlinear control algorithm for a redundant manipulator system is developed based on the Lyapunov like approach. The method considers the parametric uncertainties in the system and defines a proper filtered error signal to achieve asymptotic stability and convergence in tracking error both for the main task and sub-tasks according to the allocated priority. The performance of the proposed method is studied by some numerical simulations.

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