Advanced Control for a Chemical Process: GMC coupled with Dynamic Data Reconciliation

Kaewpradit, Pornsiri

Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659188646 / ISBN 13: 9783659188640
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Synopsis: Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. In this book, the benefits of combining dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example chemical processes. DDR is used preliminary to reconcile and estimate measured and unmeasured data required for evaluating process control or process performance. In the case studies, the robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show that a rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control.

About the Author: P. Kaewpradit is a lecturer at a Discipline of Excellence (DoE) in Chemical Engineering, Prince of Songkla University, Thailand since 2008 till now. Her professional experience is in a field of advanced control and optimization design. She is also interested in process modeling/simulation in natural rubber and palm oil.

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Title: Advanced Control for a Chemical Process: GMC...
Publisher: LAP LAMBERT Academic Publishing
Publication Date: 2012
Binding: Paperback
Book Condition: Used: Good

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Book Description Book Condition: New. Publisher/Verlag: LAP Lambert Academic Publishing | GMC coupled with Dynamic Data Reconciliation | Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. In this book, the benefits of combining dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example chemical processes. DDR is used preliminary to reconcile and estimate measured and unmeasured data required for evaluating process control or process performance. In the case studies, the robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show that a rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. | Format: Paperback | Language/Sprache: english | 172 pp. Bookseller Inventory # K9783659188640

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Book Description LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. In this book, the benefits of combining dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example chemical processes. DDR is used preliminary to reconcile and estimate measured and unmeasured data required for evaluating process control or process performance. In the case studies, the robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show that a rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. 172 pp. Englisch. Bookseller Inventory # 9783659188640

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Book Description LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. In this book, the benefits of combining dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example chemical processes. DDR is used preliminary to reconcile and estimate measured and unmeasured data required for evaluating process control or process performance. In the case studies, the robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show that a rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. 172 pp. Englisch. Bookseller Inventory # 9783659188640

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Book Description LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Book Condition: Neu. This item is printed on demand - Print on Demand Neuware - Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. In this book, the benefits of combining dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example chemical processes. DDR is used preliminary to reconcile and estimate measured and unmeasured data required for evaluating process control or process performance. In the case studies, the robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show that a rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. 172 pp. Englisch. Bookseller Inventory # 9783659188640

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Book Description LAP Lambert Academic Publishing, Germany, 2012. Paperback. Book Condition: New. Aufl.. Language: English . Brand New Book ***** Print on Demand *****.Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. In this book, the benefits of combining dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example chemical processes. DDR is used preliminary to reconcile and estimate measured and unmeasured data required for evaluating process control or process performance. In the case studies, the robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show that a rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. Bookseller Inventory # AAV9783659188640

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Book Description LAP Lambert Academic Publishing. Paperback. Book Condition: New. Paperback. 172 pages. Dimensions: 8.6in. x 5.9in. x 0.5in.Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. In this book, the benefits of combining dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example chemical processes. DDR is used preliminary to reconcile and estimate measured and unmeasured data required for evaluating process control or process performance. In the case studies, the robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show that a rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Bookseller Inventory # 9783659188640

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