Simultaneous dynamic validation/identification of mechanistic process models and reconciliation of industrial process data

Document Type

Article

Publication Date

12-1-2006

Abstract

Process models are subject to parametric uncertainty and raw process-instrumentation data are corrupted by systematic and random errors. In this work, we present a framework for dynamic parameter estimation and data reconciliation aiming at integrating model-centric support tools and industrial process operations. A realistic case-study for the rectification of the mass balance of an industrial continuous pulping system is presented. The incentive for gross-error estimation during model-based production accounting and inventory analysis is demonstrated. © 2006 Elsevier B.V. All rights reserved.

Publication Source (Journal or Book title)

Computer Aided Chemical Engineering

First Page

267

Last Page

272

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