System Identification Methods for Improving Flutter Flight Test Techniques

Abstract

Classic flutter flight testing involves the evaluation of a given configuration at a stabilized test point before clearance is given to expand the envelope further. At each stabilized point flight test data are compared with computer simulation models to assess the accuracy of predicted flutter boundaries. Because of the time constraints associated with these procedures, the Air Force has been seeking methods to improve current flight test methods. This paper describes a technique that provides a rapid, on-line tool for the identification of aeroservoelastic (ASE) systems. The technique involves the use of discrete wavelet transforms to compute the impulse response (Markov parameters) of the estimated system. This is then used in the Eigensystem Realization Algorithm (ERA) method to compute the discretized state-space matrices. The technique used herein includes metrics that are used to assess the validity of the identified system. Although the method does require that the identification begin from stabilized initial conditions, it has been shown to be relatively insensitive to input forcing function. A model of a modern naval fighter aircraft was used to evaluate the capabilities of the identification method. The identification techniques were evaluated with and without an active oscillation controller in place.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2004
Accession Number
ADA426452

Entities

People

  • Chuck Harris
  • David Klyde
  • Edward N. Bachelder
  • Peter M. Thompson

Organizations

  • Air Force Test Center

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Aircrafts
  • Algorithms
  • Altitude
  • Analog Systems
  • Boundaries
  • Control Systems
  • Convolution Integrals
  • Equations
  • Fighter Aircraft
  • Flight Control Systems
  • Frequency
  • Frequency Response
  • Oscillation
  • Time Domain
  • Wavelet Transforms

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerodynamics/Aeronautics.
  • Computational Modeling and Simulation

Technology Areas

  • Space