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Adaptive Neural Network Based Approach for Active Flow Control

  • Moshe Idan
  • Anthony J. Calise
  • Ali T. Kutai
  • David E. Parekh
Part of the International Centre for Mechanical Sciences book series (CISM, volume 439)

Abstract

This paper presents an intelligent control system architecture for micro-adaptive flow control applications. The proposed adaptive non-model based control approach is motivated by the difficulty in constructing an accurate physical model of the micro-adaptive flow control system. The control architecture employs a Neural Network based adaptive control process, and a novel method for protecting the adaptive system from poorly modeled actuator nonlinearities, such as saturation and hyteresis. We give a simple illustration of these features by considering a ducted rotor model.

Keywords

Adaptive Neural Network Model Reference Adaptive Control Active Flow Control Actuator Position Inversion Error 
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.

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Copyright information

© Springer-Verlag Wien 2003

Authors and Affiliations

  • Moshe Idan
    • 1
    • 4
  • Anthony J. Calise
    • 2
    • 4
  • Ali T. Kutai
    • 4
  • David E. Parekh
    • 3
    • 4
  1. 1.Technion — IITFaculty of Aerospace EngineeringHaifaIsrael
  2. 2.School of “Aerospace EngineeringUSA
  3. 3.Aerospace, Transportation, & Advanced Systems LaboratoryGeorgia Tech Research InstituteUSA
  4. 4.Georgia Institute of TechnologyAtlantaUSA

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