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Table of contents

  1. Front Matter
  2. Manuela L. Bujorianu, John Lygeros
    Pages 3-30
  3. Stefan Strubbe, Arjan van der Schaft
    Pages 65-104
  4. Maria Prandini, Jianghai Hu
    Pages 107-139
  5. Elena De Santis, Maria D. Di Benedetto, Stefano Di Gennaro, Alessandro D’Innocenzo, Giordano Pola
    Pages 141-170
  6. Savvas G. Loizou, Kostas J. Kyriakopoulos
    Pages 171-207
  7. Dimos V. Dimarogonas, Savvas G. Loizou, Kostas J. Kyriakopoulos
    Pages 209-253
  8. Andrea Lecchini, William Glover, John Lygeros, Jan Maciejowski
    Pages 257-276
  9. Mariken H.C. Everdij, Margriet B. Klompstra, Henk A.P. Blom, Bart Klein Obbink
    Pages 325-350
  10. François LeGland, Nadia Oudjane
    Pages 351-389
  11. Back Matter

About this book

Introduction

Stochastic hybrid systems involve the coupling of discrete (logic based), continuous and probabilistic phenomena. Because of their versatility and generality, methods for modelling and analysis of stochastic hybrid systems have proved invaluable in a wide range of applications, including finance, air traffic control, biology, telecommunications, and embedded systems. Success stories in these application areas have made stochastic hybrid systems a very important, rapidly growing and dynamic research field since the beginning of the century, bridging the gap between stochastic analysis, computer science and control engineering.
This volume presents a number of fundamental theoretical advances in the area of stochastic hybrid systems, motivated primarily from applications to air traffic management. Air traffic is arguably the most challenging application area for stochastic hybrid systems, since it requires handling complex distributed systems, multiple human in the loop elements and hybrid dynamics. The editors have collected key contributions, which define the state-of-the-art, present novel directions, and highlight emerging application areas.

Keywords

Approximation Stochastic Hybrid Control Stochastic Hybrid Systems communication control control engineering modeling optimization

Bibliographic information

  • DOI https://doi.org/10.1007/11587392
  • Copyright Information Springer-Verlag Berlin/Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-33466-8
  • Online ISBN 978-3-540-33467-5
  • Series Print ISSN 0170-8643
  • Series Online ISSN 1610-7411
  • Buy this book on publisher's site
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