The article considers the method for parametric identification of a model of steady-state modes of a technological process. The method essence is to use artificial neural networks. The input of each neural network is measured values of input and output process variables, and the output is a corresponding parameter value of the technological process model. The effectiveness of the method was assessed by conducting computational experiments on regression models with two factors and models of steady-state modes of technological processes in existing industries. The average relative error of the models does not exceed 0,43%. The method for parametric identification is applicable in adaptive control of steady-state modes of the technological process. One of advantages of the method is that with a specified form of mathematical description, training a neural network does not require statistical experimental values of process variables.

Keywords: the method for parametric identification, an artificial neural network, the model of steady-state modes of the technological process, adaptive control