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] |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
IJCT 8(3) 227-234.pdf | 1.62 MB | Adobe PDF | View/Open |
Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.