Nonlinear Model Based Process Control
Nonlinear Model Based Process Control

Author: Rıdvan Berber

Publisher: Springer Science & Business Media

Published: 1998

Total Pages: 916

ISBN-13: 9780792352204

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The increasingly competitive environment within which modern industry has to work means that processes have to be operated over a wider range of conditions in order to meet constantly changing performance targets. Add to this the fact that many industrial operations are nonlinear, and the need for on-line control algorithms for nonlinear processes becomes clear. Major progress has been booked in constrained model-based control and important issues of nonlinear process control have been solved. This text surveys the state-of-the-art in nonlinear model-based control technology, by writers who have actually created the scientific profile. A broad range of issues are covered in depth, from traditional nonlinear approaches to nonlinear model predictive control, from nonlinear process identification and state estimation to control-integrated design. Advances in the control of inverse response and unstable processes are presented. Comparisons with linear control are given, and case studies are used for illustration.

Nonlinear Model Based Process Control
Nonlinear Model Based Process Control

Author: R. Berber

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 883

ISBN-13: 940115094X

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The ASI on Nonlinear Model Based Process Control (August 10-20, 1997~ Antalya - Turkey) convened as a continuation of a previous ASI which was held in August 1994 in Antalya on Methods of Model Based Process Control in a more general context. In 1994, the contributions and discussions convincingly showed that industrial process control would increasingly rely on nonlinear model based control systems. Therefore, the idea for organizing this ASI was motivated by the success of the first one, the enthusiasm expressed by the scientific community for continuing contact, and the growing incentive for on-line control algorithms for nonlinear processes. This is due to tighter constraints and constantly changing performance objectives that now force the processes to be operated over a wider range of conditions compared to the past, and the fact that many of industrial operations are nonlinear in nature. The ASI intended to review in depth and in a global way the state-of-the-art in nonlinear model based control. The list of lecturers consisted of 12 eminent scientists leading the principal developments in the area, as well as industrial specialists experienced in the application of these techniques. Selected out of a large number of applications, there was a high quality, active audience composed of 59 students from 20 countries. Including family members accompanying the participants, the group formed a large body of92 persons. Out of the 71 participants, 11 were from industry.

Nonlinear Process Control
Nonlinear Process Control

Author: Michael A. Henson

Publisher: Prentice Hall

Published: 1997

Total Pages: 460

ISBN-13:

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Nonlinear Process Control assembles the latest theoretical and practical research on design, analysis and application of nonlinear process control strategies. It presents detailed coverage of all three major elements of nonlinear process control: identification, controller design, and state estimation. Nonlinear Process Control reflects the contributions of eleven leading researchers in the field. It is an ideal textbook for graduate courses in process control, as well as a concise, up-to-date reference for control engineers.

Advanced Control of Chemical Processes (ADCHEM'91)
Advanced Control of Chemical Processes (ADCHEM'91)

Author: K. Najim

Publisher: Elsevier

Published: 2014-05-23

Total Pages: 313

ISBN-13: 1483298973

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This volume contains 40 papers which describe the recent developments in advanced control of chemical processes and related industries. The topics of adaptive control, model-based control and neural networks are covered by 3 survey papers. New adaptive, statistical, model-based control and artificial intelligence techniques and their applications are detailed in several papers. The problem of implementation of control algorithms on a digital computer is also considered.

Methods of Model Based Process Control
Methods of Model Based Process Control

Author: R. Berber

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 814

ISBN-13: 9401101353

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Model based control has emerged as an important way to improve plant efficiency in the process industries, while meeting processing and operating policy constraints. The reader of Methods of Model Based Process Control will find state of the art reports on model based control technology presented by the world's leading scientists and experts from industry. All the important issues that a model based control system has to address are covered in depth, ranging from dynamic simulation and control-relevant identification to information integration. Specific emerging topics are also covered, such as robust control and nonlinear model predictive control. In addition to critical reviews of recent advances, the reader will find new ideas, industrial applications and views of future needs and challenges. Audience: A reference for graduate-level courses and a comprehensive guide for researchers and industrial control engineers in their exploration of the latest trends in the area.

Model Based Control
Model Based Control

Author: Paul Serban Agachi

Publisher: John Wiley & Sons

Published: 2007-09-24

Total Pages: 290

ISBN-13: 3527609229

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Filling a gap in the literature for a practical approach to the topic, this book is unique in including a whole section of case studies presenting a wide range of applications from polymerization reactors and bioreactors, to distillation column and complex fluid catalytic cracking units. A section of general tuning guidelines of MPC is also present.These thus aid readers in facilitating the implementation of MPC in process engineering and automation. At the same time many theoretical, computational and implementation aspects of model-based control are explained, with a look at both linear and nonlinear model predictive control. Each chapter presents details related to the modeling of the process as well as the implementation of different model-based control approaches, and there is also a discussion of both the dynamic behaviour and the economics of industrial processes and plants. The book is unique in the broad coverage of different model based control strategies and in the variety of applications presented. A special merit of the book is in the included library of dynamic models of several industrially relevant processes, which can be used by both the industrial and academic community to study and implement advanced control strategies.

Discrete-time Dynamic Models
Discrete-time Dynamic Models

Author: Ronald K. Pearson

Publisher: Oxford University Press, USA

Published: 1999

Total Pages: 481

ISBN-13: 0195121988

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Fueled by advances in computer technology, model-based approaches to the control of industrial processes are now widespread. While there is an enormous literature on modeling, the difficult first step of selecting an appropriate model structure has received almost no attention. This book fills the gap, providing practical insight into model selection for chemical processes and emphasizing structures suitable for control system design.

Advanced Control of Chemical Processes 1994
Advanced Control of Chemical Processes 1994

Author: D. Bonvin

Publisher: Elsevier

Published: 2014-05-23

Total Pages: 561

ISBN-13: 1483297594

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This publication brings together the latest research findings in the key area of chemical process control; including dynamic modelling and simulation - modelling and model validation for application in linear and nonlinear model-based control: nonlinear model-based predictive control and optimization - to facilitate constrained real-time optimization of chemical processes; statistical control techniques - major developments in the statistical interpretation of measured data to guide future research; knowledge-based v model-based control - the integration of theoretical aspects of control and optimization theory with more recent developments in artificial intelligence and computer science.

Advanced Chemical Process Control
Advanced Chemical Process Control

Author: Morten Hovd

Publisher: John Wiley & Sons

Published: 2023-06-02

Total Pages: 373

ISBN-13: 3527842489

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Advanced Chemical Process Control Bridge the gap between theory and practice with this accessible guide Process control is an area of study which seeks to optimize industrial processes, applying different strategies and technologies as required to navigate the variety of processes and their many potential challenges. Though the body of chemical process control theory is robust, it is only in recent decades that it has been effectively integrated with industrial practice to form a flexible toolkit. The need for a guide to this integration of theory and practice has therefore never been more urgent. Advanced Chemical Process Control meets this need, making advanced chemical process control accessible and useful to chemical engineers with little grounding in the theoretical principles of the subject. It provides a basic introduction to the background and mathematics of control theory, before turning to the implementation of control principles in industrial contexts. The result is a bridge between the insights of control theory and the needs of engineers in plants, factories, research facilities, and beyond. Advanced Chemical Process Control readers will also find: Detailed overview of Control Performance Monitoring (CPM), Model Predictive Control (MPC), and more Discussion of the cost benefit analysis of improved control in particular jobs Authored by a leading international expert on chemical process control Advanced Chemical Process Control is essential for chemical and process engineers looking to develop a working knowledge of process control, as well as for students and graduates entering the chemical process control field.

Nonlinear Model Predictive Control
Nonlinear Model Predictive Control

Author: Lalo Magni

Publisher: Springer Science & Business Media

Published: 2009-05-25

Total Pages: 562

ISBN-13: 3642010938

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Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. More than 250 papers have been published in 2006 in ISI Journals. With this book we want to bring together the contributions of a diverse group of internationally well recognized researchers and industrial practitioners, to critically assess the current status of the NMPC field and to discuss future directions and needs. The book consists of selected papers presented at the International Workshop on Assessment an Future Directions of Nonlinear Model Predictive Control that took place from September 5 to 9, 2008, in Pavia, Italy.