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Control of Distributed Parameter and Stochastic Systems

Proceedings of the IFIP WG 7.2 International Conference, June 19–22, 1998 Hangzhou, China

  • Shuping Chen
  • Xunjing Li
  • Jiongmin Yong
  • Xun Yu Zhou

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 13)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Distributed Parameter Systems

    1. Front Matter
      Pages 1-1
    2. Maïtine Bergounioux, Fredi Tröltzsch
      Pages 13-20
    3. Fariba Fahroo, Chunming Wang
      Pages 39-46
    4. Sungkwon Kang, Thomas B. Stauffer, Kirk Hatfield
      Pages 55-62
    5. Suzanne Lenhart, Min Liang, Vladimir Protopopescu
      Pages 79-84
    6. Kangsheng Liu, Zhuangyi Liu
      Pages 95-101
    7. Kangsheng Liu, David L. Russell
      Pages 103-110
    8. Boris S. Mordukhovich
      Pages 111-118
  3. Stochastic Systems

    1. Front Matter
      Pages 171-171
    2. Phillip Collings, Ulrich G. Haussmann
      Pages 189-197
    3. Yasuhiro Fujita
      Pages 207-214
    4. Hiroshi Kunita
      Pages 231-238
    5. John B. Moore, Xunyu Zhou, Andrew E. B. Lim
      Pages 247-254
    6. Jiongmin Yong
      Pages 307-314
    7. Shuping Chen, Xunjing Li, Jiongmin Yong, Xun Yu Zhou
      Pages E1-E1

About this book

Introduction

In the mathematical treatment of many problems which arise in physics, economics, engineering, management, etc., the researcher frequently faces two major difficulties: infinite dimensionality and randomness of the evolution process. Infinite dimensionality occurs when the evolution in time of a process is accompanied by a space-like dependence; for example, spatial distribution of the temperature for a heat-conductor, spatial dependence of the time-varying displacement of a membrane subject to external forces, etc. Randomness is intrinsic to the mathematical formulation of many phenomena, such as fluctuation in the stock market, or noise in communication networks. Control theory of distributed parameter systems and stochastic systems focuses on physical phenomena which are governed by partial differential equations, delay-differential equations, integral differential equations, etc., and stochastic differential equations of various types. This has been a fertile field of research with over 40 years of history, which continues to be very active under the thrust of new emerging applications.
Among the subjects covered are:
  • Control of distributed parameter systems;
  • Stochastic control;
  • Applications in finance/insurance/manufacturing;
  • Adapted control;
  • Numerical approximation
.
It is essential reading for applied mathematicians, control theorists, economic/financial analysts and engineers.

Keywords

Distribution Optimal control communication controlling manufacturing network networks service-oriented computing

Editors and affiliations

  • Shuping Chen
    • 1
  • Xunjing Li
    • 2
  • Jiongmin Yong
    • 2
  • Xun Yu Zhou
    • 3
  1. 1.Department of Applied MathematicsZhejiang UniversityHangzhouChina
  2. 2.Department of MathematicsFudan UniversityShanghaiChina
  3. 3.Department of Systems Engineering and Engineering ManagementThe Chinese University of Hong KongShatin, N.T.Hong Kong, China

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-35359-3
  • Copyright Information IFIP International Federation for Information Processing 1999
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4757-4868-0
  • Online ISBN 978-0-387-35359-3
  • Series Print ISSN 1868-4238
  • Series Online ISSN 1868-422X
  • Buy this book on publisher's site