Evaluation of parametric and nonparametric nonlinear adaptive controllers

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Abstract
In this paper, nine adaptive control algorithms are compared. The best two of them are tested experimentally. It is shown that the Adaptive FeedForward Controller AFFC) is well suited for learning the parameters of the dynamic equation, even in the presence of friction and noise. The resulting control performance is better than with measured parameters for any trajectory in the workspace. When the task consists of repeating the same trajectory, an adaptive look-up-table MEMory, introduced and analyzed in this paper, is simpler to implement and results in even better control performance.

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