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Nonlinear Model Predictive Control

Towards New Challenging Applications

  • Book
  • © 2009

Overview

Editors:
  1. Lalo Magni

    1. Dipartimento di Informatica e Sistemistica, Universita’ di Pavia, Italy

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  2. Davide Martino Raimondo

    1. Automatic Control Laboratory, ETH Zurich , Zürich, Switzerland

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  3. Frank Allgöwer

    1. Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart, Germany

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  • Assesses the current status of the NMPC field

Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 384)

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Table of contents (46 chapters)

  1. Front Matter

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  2. Stability and Robusteness

    1. Input-to-State Stability: A Unifying Framework for Robust Model Predictive Control

      • D. Limon, T. Alamo, D. M. Raimondo, D. Muñoz de la Peña, J. M. Bravo, A. Ferramosca et al.
      Pages 1-26

    2. Self-optimizing Robust Nonlinear Model Predictive Control

      • M. Lazar, W. P. M. H. Heemels, A. Jokic
      Pages 27-40

    3. Set Theoretic Methods in Model Predictive Control

      • Saša V. Raković
      Pages 41-54

    4. Adaptive Robust MPC: A Minimally-Conservative Approach

      • Darryl DeHaan, Martin Guay, Veronica Adetola
      Pages 55-67

    5. Enlarging the Terminal Region of NMPC with Parameter-Dependent Terminal Control Law

      • Shuyou Yu, Hong Chen, Christoph Böhm, Frank Allgöwer
      Pages 69-78

    6. Model Predictive Control with Control Lyapunov Function Support

      • Keunmo Kang, Robert R. Bitmead
      Pages 79-87

    7. Further Results on “Robust MPC Using Linear Matrix Inequalities”

      • M. Lazar, W. P. M. H. Heemels, D. Muñoz de la Peña, T. Alamo
      Pages 89-98

    8. LMI-Based Model Predictive Control for Linear Discrete-Time Periodic Systems

      • Christoph Böhm, Tobias Raff, Marcus Reble, Frank Allgöwer
      Pages 99-108

    9. Receding Horizon Control for Linear Periodic Time-Varying Systems Subject to Input Constraints

      • Benjamin Kern, Christoph Böhm, Rolf Findeisen, Frank Allgöwer
      Pages 109-117

  3. Control of Complex Systems

    1. Optimizing Process Economic Performance Using Model Predictive Control

      • James B. Rawlings, Rishi Amrit
      Pages 119-138

    2. Hierarchical Model Predictive Control of Wiener Models

      • Bruno Picasso, Carlo Romani, Riccardo Scattolini
      Pages 139-152

    3. Multiple Model Predictive Control of Nonlinear Systems

      • Matthew Kuure-Kinsey, B. Wayne Bequette
      Pages 153-165

    4. Stabilizing Nonlinear Predictive Control over Nondeterministic Communication Networks

      • R. Findeisen, P. Varutti
      Pages 167-179

    5. Distributed Model Predictive Control System Design Using Lyapunov Techniques

      • Jinfeng Liu, David Muñoz de la Peña, Panagiotis D. Christofides
      Pages 181-194

    6. Stabilization of Networked Control Systems by Nonlinear Model Predictive Control: A Set Invariance Approach

      • Gilberto Pin, Thomas Parisini
      Pages 195-204

    7. Nonlinear Model Predictive Control for Resource Allocation in the Management of Intermodal Container Terminals

      • A. Alessandri, C. Cervellera, M. Cuneo, M. Gaggero
      Pages 205-213

    8. Predictive Power Control of Wireless Sensor Networks for Closed Loop Control

      • Daniel E. Quevedo, Anders Ahlén, Graham C. Goodwin
      Pages 215-224

    9. On Polytopic Approximations of Systems with Time-Varying Input Delays

      • Rob Gielen, Sorin Olaru, Mircea Lazar
      Pages 225-233

  4. Stochastic Systems

    1. A Vector Quantization Approach to Scenario Generation for Stochastic NMPC

      • Graham C. Goodwin, Jan Østergaard, Daniel E. Quevedo, Arie Feuer
      Pages 235-248
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Keywords

About this book

Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. More than 250 papers have been published in 2006 in ISI Journals. With this book we want to bring together the contributions of a diverse group of internationally well recognized researchers and industrial practitioners, to critically assess the current status of the NMPC field and to discuss future directions and needs. The book consists of selected papers presented at the International Workshop on Assessment an Future Directions of Nonlinear Model Predictive Control that took place from September 5 to 9, 2008, in Pavia, Italy.

Editors and Affiliations

  • Dipartimento di Informatica e Sistemistica, Universita’ di Pavia, Italy

    Lalo Magni

  • Automatic Control Laboratory, ETH Zurich , Zürich, Switzerland

    Davide Martino Raimondo

  • Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart, Germany

    Frank Allgöwer

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