Abstract

Control of a nine-stage three-component distillation column is considered. The control objective is achieved using a neural estimator and a neural controller. The neural estimator is trained to represent the chemical process accurately, and the neural controller is trained to give an input to the chemical process which will yield the desired output. Training of both the neural networks is accomplished using a recursive least squares training algorithm implemented on an Intel iPSC/2 multicomputer (hypercube). Simulated results are presented for a numerical example.

Meeting Name

International Joint Conference on Neural Networks (1991: Jul. 8-12, Seattle, WA)

Department(s)

Mechanical and Aerospace Engineering

Second Department

Computer Science

Sponsor(s)

IEEE Technical Activities Board Council
International Neural Network Society

Keywords and Phrases

Control Systems, Nonlinear; Learning Systems; Neural Networks - Applications; Control Algorithms; Distillation Column Control; Learning Algorithms; Neural Network Controllers; Chemical Equipment

International Standard Book Number (ISBN)

0780301641

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 1992 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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