Parametric Identification of Control Systems Using Artificial Neural Networks

Abstract

For the problem of parametric identification of control objects proposed a method based on the use of artificial neural network feedforward type a perceptron. This method allows us to estimate the parameters of the mathematical model of the system with a maximum error of 2.8% and significantly reduce the time of the identification procedure.