Nonlinear Model-based Discrete-time Control of Chemical Processes
Author : Phani B. Sistu
Publisher :
Page : 157 pages
File Size : 36,58 MB
Release : 1994
Category :
ISBN :
Author : Phani B. Sistu
Publisher :
Page : 157 pages
File Size : 36,58 MB
Release : 1994
Category :
ISBN :
Author : R. Berber
Publisher : Springer Science & Business Media
Page : 883 pages
File Size : 26,18 MB
Release : 2012-12-06
Category : Science
ISBN : 940115094X
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.
Author : Rıdvan Berber
Publisher : Springer Science & Business Media
Page : 916 pages
File Size : 15,56 MB
Release : 1998
Category : Computers
ISBN : 9780792352204
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.
Author : Ronald K. Pearson
Publisher : Oxford University Press, USA
Page : 481 pages
File Size : 50,51 MB
Release : 1999
Category : Chemical process control
ISBN : 0195121988
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.
Author : Michael A. Henson
Publisher : Prentice Hall
Page : 460 pages
File Size : 47,62 MB
Release : 1997
Category : Science
ISBN :
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.
Author : Ronald K. Pearson
Publisher : Oxford University Press
Page : 481 pages
File Size : 36,55 MB
Release : 1999-12-02
Category : Mathematics
ISBN : 0195352815
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.
Author : D. Bonvin
Publisher : Elsevier
Page : 561 pages
File Size : 34,8 MB
Release : 2014-05-23
Category : Technology & Engineering
ISBN : 1483297594
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.
Author : K. Najim
Publisher : Elsevier
Page : 313 pages
File Size : 27,99 MB
Release : 2014-05-23
Category : Technology & Engineering
ISBN : 1483298973
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.
Author : R. Berber
Publisher : Springer Science & Business Media
Page : 814 pages
File Size : 45,6 MB
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9401101353
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.
Author : Paul Serban Agachi
Publisher : John Wiley & Sons
Page : 290 pages
File Size : 49,28 MB
Release : 2007-09-24
Category : Technology & Engineering
ISBN : 3527609229
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.