Robust Digital Control Design

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


An adaptive control system has to be built on top of a robust digital control system. Therefore robustness issues for the underlying controller and the shaping of the sensitivity functions for various possible values of the plant parameters are very important. After a review of some basic robustness concepts, a methodology for shaping the sensitivity functions is presented. Its application is illustrated in the context of adaptive control of a flexible transmission.


Nyquist Plot Robust Stability Sensitivity Function Pole Placement Adaptive Control System 
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.


  1. Adaptech (1988) WimPim + (includes, WinPIM, WinREG and WinTRAC) system identification and control software. User’s manual. 4, rue du Tour de l’Eau, 38400 St. Martin-d’Hères, France Google Scholar
  2. Anderson BDO, Moore J (1971) Linear optimal control. Prentice Hall, Englewood Cliffs MATHGoogle Scholar
  3. Åström KJ, Wittenmark B (1984) Computer controlled systems, theory and design. Prentice-Hall, Englewood Cliffs Google Scholar
  4. Doyle JC, Francis BA, Tannenbaum AR (1992) Feedback control theory. MacMillan, New York Google Scholar
  5. Fenot C, Rolland F, Vigneron G, Landau ID (1993) Open loop adaptive digital control in hot-dip galvanizing. Control Eng Pract 1(5):779–790 CrossRefGoogle Scholar
  6. Green M, Limebeer DJN (1995) Linear robust control. Prentice Hall, New York MATHGoogle Scholar
  7. Kwakernaak H (1993) Robust control and H -optimization—a tutorial. Automatica 29:255–273 MathSciNetMATHCrossRefGoogle Scholar
  8. Kwakernaak H (1995) Symmetries in control system design. In: Isidori A (ed) Trends in control. Springer, Heidelberg, pp 17–52 Google Scholar
  9. Landau ID (1993b) Identification et Commande des Systèmes, 2nd edn. Série Automatique. Hermès, Paris MATHGoogle Scholar
  10. Landau ID (1995) Robust digital control of systems with time delay (the Smith predictor revisited). Int J Control 62(2):325–347 MATHCrossRefGoogle Scholar
  11. Landau ID, Karimi A (1996) Robust digital control using the combined pole placement sensitivity function shaping: an analytical solution. In: Proc of WAC, vol 4, Montpellier, France, pp 441–446 Google Scholar
  12. Landau ID, Karimi A (1998) Robust digital control using pole placement with sensitivity function shaping method. Int J Robust Nonlinear Control 8:191–210 MathSciNetMATHCrossRefGoogle Scholar
  13. Landau ID, Zito G (2005) Digital control systems—design, identification and implementation. Springer, London Google Scholar
  14. Landau ID, Rey D, Karimi A, Voda-Besançon A, Franco A (1995a) A flexible transmission system as a benchmark for robust digital control. Eur J Control 1(2):77–96 Google Scholar
  15. Landau ID, Karimi A, Voda-Besançon A, Rey D (1995b) Robust digital control of flexible transmissions using the combined pole placement/sensitivity function shaping method. Eur J Control 1(2):122–133 Google Scholar
  16. Langer J, Constantinescu A (1999) Pole placement design using convex optimisation criteria for the flexible transmission benchmark: robust control benchmark: new results. Eur J Control 5(2–4):193–207 Google Scholar
  17. Langer J, Landau ID (1999) Combined pole placement/sensitivity function shaping method using convex optimization criteria. Automatica 35(6):1111–1120 MathSciNetMATHCrossRefGoogle Scholar
  18. Morari M, Zafiriou E (1989) Robust process control. Prentice Hall International, Englewood Cliffs Google Scholar
  19. Procházka H, Landau ID (2003) Pole placement with sensitivity function shaping using 2nd order digital notch filters* 1. Automatica 39(6):1103–1107 MathSciNetMATHCrossRefGoogle Scholar
  20. Sung HK, Hara S (1988) Properties of sensitivity and complementary sensitivity functions in single-input single-output digital systems. Int J Control 48(6):2429–2439 MathSciNetMATHCrossRefGoogle Scholar
  21. Zames G (1981) Feedback and optimal sensibility: model reference transformations, multiplicative seminorms and approximate inverses. IEEE Trans Autom Control 26:301–320 MathSciNetMATHCrossRefGoogle 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

Personalised recommendations