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Applying new optimization algorithms to more predictive control [electronic resource].

Published
Washington, D.C. : United States. Dept. of Energy, 1996.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description
10 pages : digital, PDF file
Additional Creators
Argonne National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary
The connections between optimization and control theory have been explored by many researchers and optimization algorithms have been applied with success to optimal control. The rapid pace of developments in model predictive control has given rise to a host of new problems to which optimization has yet to be applied. Concurrently, developments in optimization, and especially in interior-point methods, have produced a new set of algorithms that may be especially helpful in this context. In this paper, we reexamine the relatively simple problem of control of linear processes subject to quadratic objectives and general linear constraints. We show how new algorithms for quadratic programming can be applied efficiently to this problem. The approach extends to several more general problems in straightforward ways.
Report Numbers
E 1.99:mcs-p--561-0196
E 1.99: conf-960178--1
conf-960178--1
mcs-p--561-0196
Subject(s)
Other Subject(s)
Note
Published through SciTech Connect.
03/01/1996.
"mcs-p--561-0196"
" conf-960178--1"
"DE96007029"
5. chemical process control, San Francisco, CA (United States), 7-12 Jan 1996.
Wright, S.J.
Funding Information
W-31109-ENG-38
View MARC record | catkey: 14349790