Parameters estimation of nonlinear models of DC motors using neural networks

This paper considers the development of an estimation scheme for parameters of nonlinear models of DC motors using neural networks. The neural network used in this paper is a linear recurrent neural network. This scheme is considered as an online identification method based on minimization of the least square error between the actual and the estimated parameters. The stability and convergence of the proposed estimation scheme are presented. Numerical results show the effectiveness of the proposed scheme for parameters estimation of nonlinear model of a DC series motor.

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