Nonlinear dynamic data reconciliation and bias estimation of process measurements in an adiabatic stirred-tank reactor

Nonlinear dynamic data reconciliation and bias estimation of process measurements in an adiabatic stirred-tank reactor

Zobrazit všechna vydaní (2)

When process data is taken from the sensors of a plant, errors of varying degrees are inherent. Measured variables will most likely violate dynamic process models. Because of this, large volumes of data may be unreliable for process control, monitoring, and optimization. This paper describes a new m...

Celý popis

Podrobná bibliografie
Vydáno v:Philippine Engineering Journal 37, 2 (2016(D)).
Hlavní autor: Pilario, Karl Ezra S.
Další autoři: Munoz, Jose Co
Médium: Článek
Jazyk:English
Témata:
Data reconciliation.
Bias estimation.
Adiabatic.
Stirred tank reactor.
Error detection.
On-line přístup:Also available online for University of the Philippines Diliman. Click here