✦ LIBER ✦

Enhancing model predictive control using dynamic data reconciliation

✍ Scribed by Z. H. Abu-el-zeet; P. D. Roberts; V. M. Becerra

Publisher: American Institute of Chemical Engineers
Year: 2002
Tongue: English
Weight: 294 KB
Volume: 48
Category: Article
ISSN: 0001-1541
DOI: 10.1002/aic.690480216

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

The use of data reconciliation techniques can considerably reduce the inaccuracy of process data due to measurement errors. This in turn results in improved control system performance and process knowledge. Dynamic data reconciliation techniques are applied to a model‐based predictive control scheme. It is shown through simulations on a chemical reactor system that the overall performance of the model‐based predictive controller is enhanced considerably when data reconciliation is applied. The dynamic data reconciliation techniques used include a combined strategy for the simultaneous identification of outliers and systematic bias.

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