This paper proposes design details pertaining to a robust adaptive method for the compensation of uncertainties, for a class of nonlinear systems. The adaptive part of the control law uses a Gaussian network and robustness is provided by a sliding mode term. In the design, learning and control bounds are guaranteed by properly constructing the control architecture for which some methods are proposed. The robust adaptive control strategy, with the proposed design guidelines, has been validated using a hardware example case of a nonlinear electromechanical system. Experiments have shown that the inclusion of the proposed stable learning and robust terms into the control design, using the proposed constructive methods, results in improved system performance.

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