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Methods of Model Based Process Control

  • Book
  • © 1995

Overview

Editors:
  1. Ridvan Berber

    1. Department of Chemical Engineering, Ankara University, Ankara, Turkey

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Part of the book series: NATO Science Series E: (NSSE, volume 293)

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Table of contents (31 chapters)

  1. Front Matter

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

    1. Front Matter

      Pages 1-1
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    2. Towards a Process Modeling Methodolgy

      • W. Marquardt
      Pages 3-40

    3. Numerical Methods for the Simulation of Differential-Algebraic Process Models

      • W. Marquardt
      Pages 41-79

    4. Process Identification Techniques

      • Steinar Saelid
      Pages 81-97

    5. Input/Output Modeling for Process Control

      • Taylor R. Holcomb, Carl A. Rhodes, Manfred Morari
      Pages 99-109

  3. Robust Process Control

    1. Front Matter

      Pages 111-111
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    2. Frequency Domain Methods for Analysis and Design

      • Sigurd Skogestad
      Pages 113-152

    3. Frequency Domain Methods for Analysis and Design

      • Sigurd Skogestad
      Pages 153-191

    4. Mp Tuning and Synthesis

      • Mario Laiseca, Coleman Brosilow
      Pages 193-204

    5. Robust Control of Linear Time-Varying Systems with Constraints

      • Alex Zheng, Manfred Morari
      Pages 205-220

    6. New Results on Robust Controller Design for Chemical Processes

      • Ahmet PalazoÄŸlu, José A. Romagnoli
      Pages 221-234

    7. Analysis and Synthesis Methods for Robust Model Predictive Control

      • H. Gencelı, P. Vuthandam, M. Nikolaou
      Pages 235-262

    8. Attainable Performance in LQG Control

      • Bernt Lie
      Pages 263-295

  4. Advances in Model Predictive Control

    1. Front Matter

      Pages 297-297
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    2. State-Space Interpretation of Model Predictive Control

      • Jay H. Lee, Manfred Morari, Carlos E. Garcia
      Pages 299-330

    3. Topics in Model Predictive Control

      • Edward S. Meadows, James B. Rawlings
      Pages 331-347

    4. Nonlinear Moving Horizon State Estimation

      • Kenneth R. Muske, James B. Rawlings
      Pages 349-365

    5. Optimization in Model Predictive Control

      • D. Q. Mayne
      Pages 367-396

    6. Internal Model Predictive Control (IMPC)

      • Eric Coulibaly, Sandip Maiti, Coleman Brosilow
      Pages 397-425
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Keywords

About this book

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 explorationof the latest trends in the area.

Editors and Affiliations

  • Department of Chemical Engineering, Ankara University, Ankara, Turkey

    Ridvan Berber

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