NDLI: ANN based IMC scheme for CSTR

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ANN based IMC scheme for CSTR

Content Provider	ACM Digital Library
Author	Varshney, Ruchi Varshney, Tarun Sheel, Satya
Abstract	This paper demonstrates that neural networks can be used effectively for control of nonlinear dynamical systems. The proposed control scheme is based on the artificial neural network and is applied to an isothermic continuous stirred tank reactor (CSTR). In this paper we have tested the internal model control (IMC) strategy based on neural networks for process systems. This approach of control uses two Feed Forward Neural networks (FFNN), one as an identifier and the other as a controller. Multilayer neural network has been used for forward modeling and the inverse model of the process which has been determined off line using input output data of process, as controller. The modified back propagation algorithm has been used to train the neural networks. Neural network based IMC scheme has been implemented for both set point and regulatory control action and the comparison have been made for a set of constant momentum term.
Starting Page	543
Ending Page	546
Page Count	4
File Format	PDF
ISBN	9781605583518
DOI	10.1145/1523103.1523211
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-01-23
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Modified back propagation algorithm Neural networks Internal model control Cstr
Content Type	Text
Resource Type	Article

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