Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/22910
Title: ANN controller trained with steady state input-output data for a heat exchanger
Authors: Dasgupta, M S
Menon, G B
Gupta, R K
Issue Date: May-2001
Publisher: NISCAIR-CSIR, India
Abstract: This paper discusses the design and implementation of an Artificial Neural Network (ANN) based adaptive controller for a heat exchanger. The control strategy chosen is that of explicit nonlinear model predictive control. The nonlinear inverse model of the plant is identified from steady state input-output data by off-line training of a multilayered neural network through error back propagation. For performance enhancement, manipulation of training data and on-line parameter updating are tried. Single pass of derivative of error measure across the plant, on-line gave an excellent performance for regulatory as well as servo problem. The proposed cont roller is found to be successful over a wide operating range. The results are compared with that of an optimized PID controller.
Page(s): 227-234
ISSN: 0975-0991 (Online); 0971-457X (Print)
Appears in Collections:IJCT Vol.08(3) [May 2001]

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