Adaptive Feedforward Compensation of Disturbances

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


Adaptive feedforward broadband vibration (or noise) compensation is currently used when an image (a correlated measurement) of the disturbance is available. However, in most of the systems there is a “positive” feedback coupling, between the compensator system and the measurement of the image of the disturbances, which cannot be ignored. The feedforward filter should compensate for the effect of the disturbance while assuring the stability of the internal “positive” feedback loop. Algorithms for adaptive feedforward compensation in the context of this internal positive feedback will be presented and analyzed. The algorithms are evaluated in real time on an active vibration control (AVC) system using an inertial actuator.


Primary Path Active Vibration Control Secondary Path Active Noise Control Residual Acceleration 
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. Anderson BDO, Bitmead RR, Johnson CR, Kokotovic PV, Kosut R, Mareels I, Praly L, Riedle BD (1986) Stability of adaptive systems—passivity and averaging analysis. MIT Press, Cambridge Google Scholar
  2. Elliott SJ, Nelson PA (1994) Active noise control. Noise/news international, pp 75–98 Google Scholar
  3. Elliott SJ, Sutton TJ (1996) Performance of feedforward and feedback systems for active control. IEEE Trans Speech Audio Process 4(3):214–223 CrossRefGoogle Scholar
  4. Hu J, Linn JF (2000) Feedforward active noise controller design in ducts without independent noise source measurements. IEEE Trans Control Syst Technol 8(3):443–455 CrossRefGoogle Scholar
  5. Jacobson CA, Johnson CR, Cormick DCM, Sethares WA (2001) Stability of active noise control algorithms. IEEE Signal Process Lett 8(3):74–76 CrossRefGoogle Scholar
  6. Kuo MS, Morgan DR (1996) Active noise control systems-algorithms and DSP implementation. Wiley, New York Google Scholar
  7. Kuo MS, Morgan DR (1999) Active noise control: a tutorial review. Proc IEEE 87:943–973 CrossRefGoogle Scholar
  8. Landau ID, Alma M (2010) Adaptive feedforward compensation algorithms for active vibration control. In: Proc of 49th IEEE conf on decision and control, 2010, IEEE-CDC, Atlanta, USA, pp 3626–3631 Google Scholar
  9. Landau ID, Karimi A (1997b) Recursive algorithms for identification in closed loop: a unified approach and evaluation. Automatica 33(8):1499–1523 MathSciNetzbMATHCrossRefGoogle Scholar
  10. Landau ID, Karimi A, Constantinescu A (2001b) Direct controller order reduction by identification in closed loop. Automatica 37(11):1689–1702 MathSciNetzbMATHCrossRefGoogle Scholar
  11. Ljung L, Söderström T (1983) Theory and practice of recursive identification. MIT Press, Cambridge zbMATHGoogle Scholar
  12. Widrow B, Stearns SD (1985) Adaptive signal processing. Prentice-Hall, Englewood Cliffs zbMATHGoogle Scholar
  13. Zeng J, de Callafon RA (2006) Recursive filter estimation for feedforward noise cancellation with acoustic coupling. J Sound Vib 291:1061–1079 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Ioan Doré Landau
    • 1
    Email author
  • 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