Model Based Control : Case Studies in Process Engineering （2006. 350 p. w. 300 figs. 24 cm）

By Paul S. Agachi, Zoltan K. Nagy, Mircea V. Cristea et al.

WILEY-VCH（2006発売）

• 製本 Hardcover:ハードカバー版／ページ数 300 p.
• 商品コード 9783527315451

基本説明

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.

Description

(Table of content)
INTRODUCTION
Introductory Concepts of Process Control
Advanced Process Control Techniques
MODEL PREDICTIVE CONTROL
Internal Model Control
Linear Model Predictive Control
Nonlinear Model Predictive Control
MPC General Tuning Guidelines
CASE STUDIES
Productivity Optimization and Nonlinear Model - Predictive Control of a PVC Batch Reactor
Modeling, Simulation and Control of a Yeast Fermentation Bioreactor
Dynamic Modeling and Control of a High Purity Distillation Column
Practical Implementation of NMPC for a Laboratory Azeotropic Distillation Column
Model Predictive Control of the Fluid Catalytic Cracking Unit
Model Predictive Control of the Drying Process of Electric Insulators
The MPC of Brine Electrolysis Processes
(Short description)
A much-needed practical approach to the topic, this book is unique in including case studies presenting a wide range of applications for 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.
(Text)
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. 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 behavior and the economics of industrial processes and plants. Following a section on general tuning guidelines of MPC, the text covers distributed control systems and FCCU MPC as well as their practical implementation. A library of dynamic models of several processes is also included.