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Title: Adaptive model predictive control using neural networks

Abstract

The authors work in controlling chemical processes included the following: (1) to develop neural networks and training procedures that are well suited to: small amounts of off-line training data for on-line control of systems with substantial time lags; (2) to develop generic Model Predictive Control (MPC) software; and (3) to control the following simulated systems using MPC: continuously stirred tank reactor with jacket dynamics; plasma etching model for semiconductor manufacture; and distillation columns. Details descriptions are given of the three points.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Los Alamos National Lab., NM (United States)
Sponsoring Org.:
USDOE, Washington, DC (United States)
OSTI Identifier:
10178912
Report Number(s):
LA-UR-94-2725
ON: DE94018086; TRN: AHC29420%%50
DOE Contract Number:  
W-7405-ENG-36
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: [1994]
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; CHEMICAL REACTORS; ON-LINE CONTROL SYSTEMS; DISTILLATION EQUIPMENT; NEURAL NETWORKS; TRAINING; INDUSTRIAL PLANTS; SEMICONDUCTOR DEVICES; 320303; 990200; EQUIPMENT AND PROCESSES; MATHEMATICS AND COMPUTERS

Citation Formats

Baum, C C, Buescher, K L, Hanagandi, V, Jones, R, and Lee, K. Adaptive model predictive control using neural networks. United States: N. p., 1994. Web. doi:10.2172/10178912.
Baum, C C, Buescher, K L, Hanagandi, V, Jones, R, & Lee, K. Adaptive model predictive control using neural networks. United States. doi:10.2172/10178912.
Baum, C C, Buescher, K L, Hanagandi, V, Jones, R, and Lee, K. Thu . "Adaptive model predictive control using neural networks". United States. doi:10.2172/10178912. https://www.osti.gov/servlets/purl/10178912.
@article{osti_10178912,
title = {Adaptive model predictive control using neural networks},
author = {Baum, C C and Buescher, K L and Hanagandi, V and Jones, R and Lee, K},
abstractNote = {The authors work in controlling chemical processes included the following: (1) to develop neural networks and training procedures that are well suited to: small amounts of off-line training data for on-line control of systems with substantial time lags; (2) to develop generic Model Predictive Control (MPC) software; and (3) to control the following simulated systems using MPC: continuously stirred tank reactor with jacket dynamics; plasma etching model for semiconductor manufacture; and distillation columns. Details descriptions are given of the three points.},
doi = {10.2172/10178912},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1994},
month = {9}
}