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Assessment and Future Directions of Nonlinear Model Predictive Control

  • Book
  • © 2007

Overview

Editors:
  1. Rolf Findeisen

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

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  2. Frank Allgöwer

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

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  3. Lorenz T. Biegler

    1. Chemical Engineering Department, Carnegie Mellon University, Pittsburgh, USA

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  • Results of the international workshop entitled "Assesmentand Future Directions of Nonlinear Model Predictive Control” (NMPC´05), which was held in Freudenstadt-Lauterbad, Germany on August 26-30, 2005

Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 358)

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Table of contents (53 chapters)

  1. Front Matter

    Pages I-XII
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  2. Foundations and History of NMPC

    1. Nonlinear Model Predictive Control: An Introductory Review

      • Eduardo F. Camacho, Carlos Bordons
      Pages 1-16

  3. Theoretical Aspects of NMPC

    1. Hybrid MPC: Open-Minded but Not Easily Swayed

      • S. Emre Tuna, Ricardo G. Sanfelice, Michael J. Messina, Andrew R. Teel
      Pages 17-34

    2. Conditions for MPC Based Stabilization of Sampled-Data Nonlinear Systems Via Discrete-Time Approximations

      • Eva Gyurkovics, Ahmed M. Elaiw
      Pages 35-48

    3. A Computationally Efficient Scheduled Model Predictive Control Algorithm for Control of a Class of Constrained Nonlinear Systems

      • Mayuresh V. Kothare, Zhaoyang Wan
      Pages 49-62

    4. The Potential of Interpolation for Simplifying Predictive Control and Application to LPV Systems

      • John Anthony Rossiter, Bert Pluymers, Bart De Moor
      Pages 63-76

    5. Techniques for Uniting Lyapunov-Based and Model Predictive Control

      • Prashant Mhaskar, Nael H. El-Farra, Panagiotis D. Christofides
      Pages 77-91

    6. Discrete-Time Non-smooth Nonlinear MPC: Stability and Robustness

      • M. Lazar, W. P. M. H. Heemels, A. Bemporad, S. Weiland
      Pages 93-103

    7. Model Predictive Control for Nonlinear Sampled-Data Systems

      • L. GrĂĽne, D. Nešić, J. Pannek
      Pages 105-113

    8. Sampled-Data Model Predictive Control for Nonlinear Time-Varying Systems: Stability and Robustness

      • Fernando A. C. C. Fontes, Lalo Magni, Eva Gyurkovics
      Pages 115-129

    9. On the Computation of Robust Control Invariant Sets for Piecewise Affine Systems

      • T. Alamo, M. Fiacchini, A. Cepeda, D. Limon, J. M. Bravo, E. F. Camacho
      Pages 131-139

    10. Nonlinear Predictive Control of Irregularly Sampled Data Systems Using Identified Observers

      • Meka Srinivasarao, Sachin C. Patwardhan, R. D. Gudi
      Pages 141-149

    11. Nonlinear Model Predictive Control: A Passivity-Based Approach

      • Tobias Raff, Christian Ebenbauer, Prank Allgöwer
      Pages 151-162

  4. Numerical Aspects of NMPC

    1. Numerical Methods for Efficient and Fast Nonlinear Model Predictive Control

      • Hans Georg Bock, Moritz Diehl, Peter KĂĽhl, Ekaterina Kostina, Johannes P. Schiöder, Leonard Wirsching
      Pages 163-179

    2. Computational Aspects of Approximate Explicit Nonlinear Model Predictive Control

      • Alexandra Grancharova, Tor A. Johansen, Petter Tøndel
      Pages 181-192

    3. Towards the Design of Parametric Model Predictive Controllers for Non-linear Constrained Systems

      • V. Sakizlis, K. I. Kouramas, N. P. Faisca, E. N. Pistikopoulos
      Pages 193-205

    4. Interior-Point Algorithms for Nonlinear Model Predictive Control

      • Adrian G. Wills, William P. Heath
      Pages 207-216

    5. Hard Constraints for Prioritized Objective Nonlinear MPC

      • Christopher E. Long, Edward P. Gatzke
      Pages 217-228

    6. A Nonlinear Model Predictive Control Framework as Free Software: Outlook and Progress Report

      • Andrey Romanenko, Lino O. Santos
      Pages 229-238

  5. Robustness, Robust Design, and Uncertainty

    1. Robustness and Robust Design of MPC for Nonlinear Discrete-Time Systems

      • Lalo Magni, Riccardo Scattolini
      Pages 239-254
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Keywords

About this book

Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.

Reviews

“It is a wide ranging text covering such areas as hybrid systems, constrained control, LPV systems, nonlinear discrete-time systems and many others. … This is a valuable contribution to the subject and is suitable for researchers and engineers involved in all aspects of nonlinear MPC design and implementation.” (ACTC applied control technology consortium, actc-control.com, March, 2016)

Editors and Affiliations

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

    Rolf Findeisen, Frank Allgöwer

  • Chemical Engineering Department, Carnegie Mellon University, Pittsburgh, USA

    Lorenz T. Biegler

Bibliographic Information

  • Book Title: Assessment and Future Directions of Nonlinear Model Predictive Control

  • Editors: Rolf Findeisen, Frank Allgöwer, Lorenz T. Biegler

  • Series Title: Lecture Notes in Control and Information Sciences

  • DOI: https://doi.org/10.1007/978-3-540-72699-9

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2007

  • Softcover ISBN: 978-3-540-72698-2Published: 05 July 2007

  • eBook ISBN: 978-3-540-72699-9Published: 08 September 2007

  • Series ISSN: 0170-8643

  • Series E-ISSN: 1610-7411

  • Edition Number: 1

  • Number of Pages: XII, 644

  • Topics: Control, Robotics, Mechatronics, Systems Theory, Control

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