Large-Scale Parameter Estimation in Low-Density Polyethylene Tubular Reactors

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• 作者：Victor M. Zavala ; Lorenz T. Biegler
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2006
• 出版时间：November 8, 2006
• 年：2006
• 卷：45
• 期：23
• 页码：7867 - 7881
• 全文大小：175K
• 年卷期：v.45,no.23(November 8, 2006)
• ISSN：1520-5045

文摘

We propose a simultaneous approach for the solution of the associated DAE-constrained parameter estimationproblem. Parameter estimation is an essential task in the development and on-line update of first-principlesmodels for low-density polyethylene tubular reactors, consisting of nonlinear and stiff differential-algebraicequations (DAE). Our approach discretizes the reactor model equations in space, leading to a large-scalenonlinear program (NLP) that can be solved efficiently with state-of-the-art general-purpose NLP solvers. Indoing so, more efficient estimation strategies can be considered, enabling the solution of challenging estimationproblems including multiple data and large parameters sets. This approach is efficient in handling advancedregression problems such as the errors-in-variables-measured (EVM) formulation. The methodology is fast,robust, and reliable and can be used both for off-line and on-line purposes. Moreover, substantial improvementson the reactor model predictions have been obtained over previous approaches, making the model amenablefor real-time optimization and control tasks.