Modeling And Advanced Control For Process Industries


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Modeling and Advanced Control for Process Industries


Modeling and Advanced Control for Process Industries

Author: Ming Rao

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-03-07


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Due to the complexity of the process operation and the requirements for high quality, low cost, safety and the protection of the environment, an increasing number of pulp and paper companies are in need of an advanced control technology to improve their process operation. This publication presents, for the first time, the theory of such an advanced control technology as well as various industrial applications associated especially with Paper Making. The reader will gain a better understanding of the most popular and advanced process control techniques and applications of these techniques in an important real-time process industry. The contents are based on the authors' own research on modeling and advanced control in this field.

Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing


Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing

Author: Y. A. Liu

language: en

Publisher: John Wiley & Sons

Release Date: 2023-07-25


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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing Detailed resource on the “Why,” “What,” and “How” of integrated process modeling, advanced control and data analytics explained via hands-on examples and workshops for optimizing polyolefin manufacturing. Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing discusses, as well as demonstrates, the optimization of polyolefin production by covering topics from polymer process modeling and advanced process control to data analytics and machine learning, and sustainable design and industrial practice. The text also covers practical problems, handling of real data streams, developing the right level of detail, and tuning models to the available data, among other topics, to allow for easy translation of concepts into practice. Written by two highly qualified authors, Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing includes information on: Segment-based modeling of polymer processes; selection of thermodynamic methods; estimation of physical properties for polymer process modeling Reactor modeling, convergence tips and data-fit tool; free radical polymerization (LDPE, EVA and PS), Ziegler-Natta polymerization (HDPE, PP, LLPDE, and EPDM) and ionic polymerization (SBS rubber) Improved polymer process operability and control through steady-state and dynamic simulation models Model-predictive control of polyolefin processes and applications of multivariate statistics and machine learning to optimizing polyolefin manufacturing Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing enables readers to make full use of advanced computer models and latest data analytics and machine learning tools for optimizing polyolefin manufacturing, making it an essential resource for undergraduate and graduate students, researchers, and new and experienced engineers involved in the polyolefin industry.

Process Dynamics and Control


Process Dynamics and Control

Author: Brian Roffel

language: en

Publisher: John Wiley & Sons

Release Date: 2007-01-11


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Offering a different approach to other textbooks in the area, this book is a comprehensive introduction to the subject divided in three broad parts. The first part deals with building physical models, the second part with developing empirical models and the final part discusses developing process control solutions. Theory is discussed where needed to ensure students have a full understanding of key techniques that are used to solve a modeling problem. Hallmark Features: Includes worked out examples of processes where the theory learned early on in the text can be applied. Uses MATLAB simulation examples of all processes and modeling techniques- further information on MATLAB can be obtained from www.mathworks.com Includes supplementary website to include further references, worked examples and figures from the book This book is structured and aimed at upper level undergraduate students within chemical engineering and other engineering disciplines looking for a comprehensive introduction to the subject. It is also of use to practitioners of process control where the integrated approach of physical and empirical modeling is particularly valuable.