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Abstract: This paper proposes an online training scheme for RBFNN (Radial Basis Function Neural Network) based sliding mode controller to Control the robot manipulator. The approach is based on a sliding mode control methodology which drives the system towards a sliding surface by tuning the parameters of the controller using Gaussian radial basis function neural network. The key feature of this scheme is that prior knowledge of the system uncertainties is not required to guarantee the stability. Also the chattering phenomenon is completely eliminated. To demonstrate the effectiveness of the proposed approach, a three link Scara robot is simulated in the presence of uncertainties.