Results of research on control object identification based on neural network processes modeling are given. Model of object with control system is represented with a dynamic neural network and regulator model. Regulator function is known. Neural network is trained on the data of control object operating. The resulting model simulate the behavior of the system and lets us find the system’s output, including outputs for periodic test influences. By the resulting complex frequency response we find the parameters of the channel. Observed objects represent technological processes with continuous production. We show an example of identification for laboratory control object channel.

Keywords: Object with control system, identification, neural network, modeling, complex frequency response, transfer function