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Steady-state optimizing control of a group of chemical processes

✍ Scribed by R. Tavast


Publisher
Elsevier Science
Year
1972
Tongue
English
Weight
962 KB
Volume
8
Category
Article
ISSN
0005-1098

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✦ Synopsis


In a centralized control system of chemical production processes the common stochastic optimization problem can be adapted to the peculiarities and variability of each individual process.

Smnmary--This paper is devoted to steady-state optimizing control of a group of single-reactor continuous chemical processes. A generalized model has been developed, based on the heat and mass balance equations in matrix form. The least squares estimators of the process variables are presented. The optimization problem is formulated as a chance constrained programming problem under uncertainty and its "confidence equivalent" is proposed.

An open-loop system has been developed for set-point control of a group of formaldehyde processes using a Minsk-32 computer, telegraph lines and remote terminals, and the application patterns are given.

NOTATIONAL CONVENTIONS

Matrices are upper case bold-faced letters Vectors are lower case bold-faced letters Apostrophe (') denotes matrix transposition Vectors are assumed to be columns, x j denotes the fith component of x denotes the fl-th column of a matrix B D(x) denotes diagonal matrix with a vector x on its principal diagonal ec is the unit c-vector I is the unit matrix of appropriate dimensions and ~ denote the measured and estimated values of g respectively m~ and s~ are the estimates of the mean and variance of y~ Pr [.] and E[.] denote the probability and expectation respectively y~Nc(.) means that y has c-dimensional gaussian distribution *


πŸ“œ SIMILAR VOLUMES


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Brief Paper Dynamic Version of Steady State Optimizing Control of a Distillation Column by Trial Method\* Version dynamique de la commande optimalisante en rrgime &abli d'une colonne distiller par la m&hode d'exploration Dynamische Variante einer den station/iren Zustand optimierenden Regelung einer

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## Abstract Methods are presented for the design of a static estimator which infers unmeasurable product qualities from secondary measurements. The secondary measurements are selected so as to minimize the number of such measurements required to obtain an accurate estimate which is insensitive to m