Model-based Predictive Control for the Exhaust Gas Cycle of an Oxyfuel-Process

Nötges, Thomas; Hölemann, Sebastian; Abel, Dirk

doi:10.3182/20080706-5-kr-1001.01848

Cited by 2 publications

(2 citation statements)

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“…2. The system is part of a novel zero-emission fossil power plant concept based on an oxyfuel combustion, which is currently researched at the RWTH Aachen University (see [9]). The sketched process supplies a gas mixture of oxygen and carbon dioxide for burning the combustible.…”

Section: Application To An Oxyfuel Processmentioning

confidence: 99%

“…The high temperatures are obtained by recirculating exhaust gas from the combustion chamber by the exhaust gas blower and conducting it through the membrane, where it is oxygenated to be reused as combustion gas. A detailed description of the entire oxyfuel process and its nonlinear modeling in Modelica can be found in [9]. Here, a simplified process is considered, where the exhaust gas is gathered from a sink with constant pressure, temperature and gas composition.…”

Section: Description Of the Plantmentioning

confidence: 99%

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Modelica Predictive Control – An MPC Library for ModelicaEine MPC-Bibliothek für Modelica

Hölemann¹,

Abel

2009

At - Automatisierungstechnik

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Modelica is a powerful and flexible instrument for component-wise dynamic system modeling. Unfortunately, until now it does not provide many structures to integrate advanced control methods. This article presents a Modelica library for model-based predictive controllers with linear process models, which offers the use of several model representations in the controller for predicting the future plant outputs. As well, the controller is capable of constraints and disturbance handling. A controller block can be included easily into any Modelica model and is parameterized intuitively. The library avoids the coupling of Modelica to other software products.Thus, a contribution is made towards an integrated control system design in Modelica.Modelica ist eine mächtige und flexible Lösung zur objektorientierten komponentenweisen Modellierung dynamischer Systeme. Allerdings bietet es bislang nur wenige Ansätze höhere Regelungsverfahren zu integrieren. In diesem Artikel wird eine Modelica Bibliothek für modellgestütze prädiktive Regler vorgestellt, die die Verwendung verschiedener linearer Modellrepräsentationen zur Prädiktion der zukünftigen Regelgrößen ermöglicht. Weiterhin kann der Regler Beschränkungen und Störgrößen behandeln. Ein Reglerblock kann leicht in jedes Modelica Modell eingefügt werden und ist intuitiv parametrierbar. Die Bibliothek erspart die oftmals schwierige Kopplung von Modelica zu anderen Softwarepaketen. Sie leistet daher einen Beitrag zum durchgängigen Reglerentwurf mit Modelica.

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Section: Application To An Oxyfuel Processmentioning

confidence: 99%

Section: Description Of the Plantmentioning

confidence: 99%