Methods of Model Based Process Control

  • Ridvan Berber

Part of the NATO ASI Series book series (NSSE, volume 293)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Process Modeling, Dynamic Simulation and Identification

    1. Front Matter
      Pages 1-1
    2. W. Marquardt
      Pages 3-40
    3. Steinar Saelid
      Pages 81-97
    4. Taylor R. Holcomb, Carl A. Rhodes, Manfred Morari
      Pages 99-109
  3. Robust Process Control

    1. Front Matter
      Pages 111-111
    2. Sigurd Skogestad
      Pages 113-152
    3. Sigurd Skogestad
      Pages 153-191
    4. Mario Laiseca, Coleman Brosilow
      Pages 193-204
    5. Alex Zheng, Manfred Morari
      Pages 205-220
    6. Ahmet Palazoğlu, José A. Romagnoli
      Pages 221-234
    7. H. Gencelı, P. Vuthandam, M. Nikolaou
      Pages 235-262
    8. Bernt Lie
      Pages 263-295
  4. Advances in Model Predictive Control

    1. Front Matter
      Pages 297-297
    2. Jay H. Lee, Manfred Morari, Carlos E. Garcia
      Pages 299-330
    3. Edward S. Meadows, James B. Rawlings
      Pages 331-347
    4. Kenneth R. Muske, James B. Rawlings
      Pages 349-365
    5. D. Q. Mayne
      Pages 367-396
    6. Eric Coulibaly, Sandip Maiti, Coleman Brosilow
      Pages 397-425

About this book

Introduction

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.

Keywords

design fuzzy model modeling numerical methods optimization polymer simulation

Editors and affiliations

  • Ridvan Berber
    • 1
  1. 1.Department of Chemical EngineeringAnkara UniversityAnkaraTurkey

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-011-0135-6
  • Copyright Information Kluwer Academic Publishers 1995
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-4061-7
  • Online ISBN 978-94-011-0135-6
  • Series Print ISSN 0168-132X
  • About this book
Industry Sectors
Pharma
Automotive
Chemical Manufacturing
Biotechnology
Electronics
Consumer Packaged Goods
Energy, Utilities & Environment
Aerospace
Oil, Gas & Geosciences
Engineering