Developments in Model-Based Optimization and Control

Distributed Control and Industrial Applications

  • Sorin Olaru
  • Alexandra Grancharova
  • Fernando Lobo Pereira

Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 464)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Complexity and Structural Properties of Linear Model Predictive Control

    1. Front Matter
      Pages 1-1
    2. Ngoc Anh Nguyen, Sorin Olaru, Pedro Rodriguez-Ayerbe, Morten Hovd, Ion Necoara
      Pages 27-47
    3. Martin Gulan, Ngoc Anh Nguyen, Sorin Olaru, Pedro Rodriguez-Ayerbe, Boris Rohal’-Ilkiv
      Pages 49-70
  3. Distributed-coordinated and Multi-objective Features of Model Predictive Control

    1. Front Matter
      Pages 71-71
    2. John Sandoval-Moreno, John Jairo Martínez, Gildas Besançon
      Pages 93-114
    3. Julián Barreiro-Gomez, Carlos Ocampo-Martinez, Nicanor Quijano
      Pages 115-138
  4. Collaborative Model Predictive Control

    1. Front Matter
      Pages 139-139
    2. Alessandro Rucco, António Pedro Aguiar, Fernando A. C. C. Fontes, Fernando Lobo Pereira, João Borges de Sousa
      Pages 141-160
    3. Ionela Prodan, Sorin Olaru, Fernando A.C.C. Fontes, Fernando Lobo Pereira, João Borges de Sousa, Cristina Stoica Maniu et al.
      Pages 161-181
    4. Minh Tri Nguyen, Cristina Stoica Maniu, Sorin Olaru, Alexandra Grancharova
      Pages 183-205
  5. Applications of Optimization-Based Control and Identification

    1. Front Matter
      Pages 207-207
    2. Sihem Tebbani, Mariana Titica, George Ifrim, Marian Barbu, Sergiu Caraman
      Pages 209-235
    3. Dorin Şendrescu, Sihem Tebbani, Dan Selişteanu
      Pages 237-254
  6. Optimization-Based Analysis and Design for Particular Classes of Dynamical Systems

    1. Front Matter
      Pages 275-275
    2. Fernando Lobo Pereira, Fernando A. C. C. Fontes, António Pedro Aguiar, João Borges de Sousa
      Pages 277-300
    3. Franco Blanchini, Daniele Casagrande, Giulia Giordano, Stefano Miani
      Pages 319-338
  7. Back Matter
    Pages 379-381

About this book


This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design.

Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization.

The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on:

· complexity and structure in model predictive control (MPC);

· collaborative MPC;

· distributed MPC;

· optimization-based analysis and design; and

· applications to bioprocesses, multivehicle systems or energy management.

The various contributions cover a subject spectrum including inverse optimality and more modern decentralized and cooperative formulations of receding-horizon optimal control. Readers will find fourteen chapters dedicated to optimization-based tools for robustness analysis, and decision-making in relation to feedback mechanisms—fault detection, for example—and three chapters putting forward applications where the model-based optimization brings a novel perspective.

Developments in Model-Based Optimization and Control is a selection of contributions expanded and updated from the Optimisation-based Control and Estimation workshops held in November 2013 and November 2014. It forms a useful resource for academic researchers and graduate students interested in the state of the art in predictive control. Control engineers working in model-based optimization and control, particularly in its bioprocess applications will also find this collection instructive.


Bioprocesses Constrained Estimation Constrained and Predictive Control Control of Impulsive Systems Coordinated Control Distributed Predictive Control Fault-tolerant Control Model Predictive Control Multiagent Dynamical Systems Optimal Control Optimization-based Control Robustness in Constrained Control Set Invariance Unmanned Robotic Vehicle Systems

Editors and affiliations

  • Sorin Olaru
    • 1
  • Alexandra Grancharova
    • 2
  • Fernando Lobo Pereira
    • 3
  1. 1.Laboratory of Signals and SystemsCentraleSupélec-CNRS-Université Paris-Sud, Université Paris-SaclayGif sur YvetteFrance
  2. 2.Department of Industrial AutomationUniv. of Chem.Tech. and Metallurgy Department of Industrial AutomationSofiaBulgaria
  3. 3.Faculty of EngineeringPorto University Faculty of EngineeringPortoPortugal

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-26685-5
  • Online ISBN 978-3-319-26687-9
  • Series Print ISSN 0170-8643
  • Series Online ISSN 1610-7411
  • Buy this book on publisher's site