Model based control : (Record no. 23388)

MARC details
000 -LEADER
fixed length control field 04055cam a22002657a 4500
001 - CONTROL NUMBER
control field vtls000002956
003 - CONTROL NUMBER IDENTIFIER
control field VRT
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250102224916.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 081214s2006 gw a |b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 3527315454 (cased)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783527315451 (cased)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201402040106
Level of effort used to assign nonsubject heading access points VLOAD
Level of effort used to assign subject headings 201007311028
Level of effort used to assign classification malmash
Level of effort used to assign subject headings 200812141105
Level of effort used to assign classification musallam
-- 200812140942
-- alawaid
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TP155.75
Item number .M62 2006
245 00 - TITLE STATEMENT
Title Model based control :
Remainder of title case studies in process engineering /
Statement of responsibility, etc. Paul Serban Agachi ... [et al.].
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Weinheim :
Name of publisher, distributor, etc. Wiley-VCH,
Date of publication, distribution, etc. c2006.
300 ## - PHYSICAL DESCRIPTION
Extent xi, 277 p. :
Other physical details ill. ;
Dimensions 25 cm.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Preface. 1 Introduction. 1.1 Introductory Concepts of Process Control. 1.2 Advanced Process Control Techniques. 1.2.1 Key Problems in Advanced Control of Chemical Processes. 1.2.1.1 Nonlinear Dynamic Behavior. 1.2.1.2 Multivariable Interactions between Manipulated and Controlled Variables. 1.2.1.3 Uncertain and Time-Varying Parameters. 1.2.1.4 Deadtime on Inputs and Measurements. 1.2.1.5 Constraints on Manipulated and State Variables. 1.2.1.6 High-Order and Distributed Processes. 1.2.1.7 Unmeasured State Variables and Unmeasured and Frequent Disturbances. 1.2.2 Classification of the Advanced Process Control Techniques. 2 Model Predictive Control. 2.1 Internal Model Control. 2.2 Linear Model Predictive Control. 2.3 Nonlinear Model Predictive Control. 2.3.1 Introduction. 2.3.2 Industrial Model-Based Control: Current Status and Challenges. 2.3.2.1 Challenges in Industrial NMPC. 2.3.3 First Principle (Analytical) Model-Based NMPC. 2.3.4 NMPC with Guaranteed Stability. 2.3.5 Artificial Neural Network (ANN)-Based Nonlinear Model Predictive Control. 2.3.5.1 Introduction. 2.3.5.2 Basics of ANNs. 2.3.5.3 Algorithms for ANN Training. 2.3.5.4 Direct ANN Model-Based NMPC (DANMPC). 2.3.5.5 Stable DANMPC Control Law. 2.3.5.6 Inverse ANN Model-Based NMPC. 2.3.5.7 ANN Model-Based NMPC with Feedback Linearization. 2.3.5.8 ANN Model-Based NMPC with On-Line Linearization. 2.3.6 NMPC Software for Simulation and Practical Implementation. 2.3.6.1 Computational Issues. 2.3.6.2 NMPC Software for Simulation. 2.3.6.3 NMPC Software for Practical Implementation. 2.4 MPC General Tuning Guidelines. 2.4.1 Model Horizon (n). 2.4.2 Prediction Horizon (p). 2.4.3 Control Horizon (m). 2.4.4 Sampling Time (T). 2.4.5 Weight Matrices ( l y and l u). 2.4.6 Feedback Filter. 2.4.7 Dynamic Sensitivity Used for MPC Tuning. 3 Case Studies. 3.1 Productivity Optimization and Nonlin
520 ## - SUMMARY, ETC.
Summary, etc. 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Chemical process control
Form subdivision Case studies.
9 (RLIN) 49364
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Predictive control
Form subdivision Case studies.
9 (RLIN) 49365
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Chemical engineering.
9 (RLIN) 6532
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Agachi, Paul Serban.
9 (RLIN) 49366
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Suppress in OPAC No
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Library of Congress Classification     Library Library First Floor 21/12/2024   TP155.75 .M62 2006 8955 21/12/2024 1 21/12/2024 Books
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