Neural network nonlinear plant identification as a tool in intelligent controller design

This article discusses the practical aspects of using neural networks in the identification of nonlinear industrial plants through the use of closed-loop operation data, with the purpose of creating a computational model that facilitates the development and tuning of intelligent control algorithms. In this paper, specifically, an oil separation plant is identified and the resulting model is employed to develop a fuzzy logic controller.