Model Identification and Validation for a Nonlinear Process Using Recurrent Neural Networks

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Provided by: International Journal of Research in Electronics and Computer Engineering (IJRECE)
Topic: Networking
Format: PDF
System identification of non-linear process system is important and beneficial in the process industries. The main objective for the modeling task is to obtain a good and reliable tool for analysis and control system development. In this paper, a model identification of a nonlinear process is performed by Nonlinear AutoRegressive eXogenous (NARX) recurrent neural network and Elman Recurrent Neural Network (ERNN) approach. Developed models performance is analyzed and best among them can be used in off-line controller design and implementation of new advanced control schemes.
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