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Discrete-Time System Models for Control

  • Ioan Doré Landau
  • Rogelio Lozano
  • Mohammed M’Saad
  • Alireza Karimi
Part of the Communications and Control Engineering book series (CCE)

Abstract

This chapter reviews the discrete-time systems models which will be used throughout the book as well as the computation of predictors in a deterministic and stochastic environment.

Keywords

Stochastic Environment Stochastic Disturbance State Estimation Error Optimal Predictor Auto Regressive Move Average 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Åström KJ (1970) Introduction to stochastic control theory. Academic Press, New York MATHGoogle Scholar
  2. Åström KJ, Hagander P, Sternby J (1984) Zeros of sampled systems. Automatica 20:31–38 MATHCrossRefGoogle Scholar
  3. Faurre P, Clerget M, Germain F (1979) Opérateurs rationnels positifs: Application à l’hyperstabilité et aux processus aléatoires. Bordas, Paris MATHGoogle Scholar
  4. Goodwin GC, Sin KS (1984) Adaptive filtering prediction and control. Prentice Hall, New York MATHGoogle Scholar
  5. Kailath T (1980) Linear systems. Prentice-Hall, New York MATHGoogle Scholar
  6. Wolowich WA (1974) Linear multivariable systems. Springer, Heidelberg Google Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Ioan Doré Landau
    • 1
  • Rogelio Lozano
    • 2
  • Mohammed M’Saad
    • 3
  • Alireza Karimi
    • 4
  1. 1.Département d’AutomatiqueGIPSA-LAB (CNRS/INPG/UJF)St. Martin d’HeresFrance
  2. 2.UMR-CNRS 6599, Centre de Recherche de Royalieu, Heuristique et Diagnostic des Systèmes ComplexesUniversité de Technologie de CompiègneCompiègneFrance
  3. 3.Centre de Recherche (ENSICAEN), Laboratoire GREYCÉcole Nationale Supérieure d’Ingénieurs de CaenCaen CedexFrance
  4. 4.Laboratoire d’AutomatiqueÉcole Polytechnique Fédérale de LausanneLaussanneSwitzerland

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