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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
AIChE Journal
Article . 1988 . Peer-reviewed
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Nonlinear inferential control

Authors: J. R. Parrish; C. B. Brosilow;

Nonlinear inferential control

Abstract

AbstractNonlinear inferential control (NLIC) has been developed as a method for improving control of nonlinear systems. The controller is modelbased, and allows for direct use of available measurements. This paper presents the structure of NLIC and the manner in which it is applied to processes when the controlled variables are measured. Also described is the improvement in the process control using NLIC. Two illustrative examples are presented, a laboratory heat exchanger process and a simulated neutralization process. The results indicate that a substantial improvement in control is possible using NLIC.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
65
Top 10%
Top 1%
Top 10%
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