AIAA-2004-6838-498 - AIAA 2004-6838 USAF Developmental Test...

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American Institute of Aeronautics and Astronautics 1 Wavelet-Based Techniques for Improved On-Line Systems Identification Peter M. Thompson, Ph.D. * , Edward N. Bachelder, Ph.D. , David H. Klyde Systems Technology, Inc., Hawthorne, CA, 90250 Chuck Harris, Ph.D. § 412 TW/ENTT, Air Force Flight Test Center, Edwards AFB, CA, 93524 and Martin J. Brenner ƒ NASA Dryden Flight Research Center, Edwards AFB, CA, 93523 Wavelet transform methods can be used to rapidly identify the frequency response of aerospace vehicles using on-line time series for selected input/output pairs. These methods are an alternative to windowed Fourier transforms, the main difference being that wavelet transforms more rapidly identify changes in the vehicle response at high frequency, and thus are more suited to problems such as failure detection, loss of control detection, and flutter detection. Identification methods based on wavelet transforms can improve flight safety and increase the efficiency of on-line flight test analysis methods. Two wavelet-based methods are described in this paper, with examples and a discussion of how they are implemented. In the first method the frequency response is estimated using ratios of wavelet transforms, and is recommended for use when the input spectrum is broadband and for piloted input during normal operations. In the second method the wavelets are used as a front end to the Eigensystem Realization Algorithm, and is recommended for system identification when using short duration, discrete inputs such as steps and doublets. Windowed Fourier transform methods remain the recommended choice for longer duration, discrete inputs such as frequency sweeps. I. Introduction he objective of recent work at Systems Technology, Inc. has been to develop wavelet-based methods for system identification and then to apply these methods to a broad range of refractory automatic and manual control system problems. These control problems are those that escape detection by typical design criteria and methodologies, surface under unusual or rare circumstances, and threaten flight safety. Examples include hardware failures, unexpected transitions in multimode flight control software, the onset of flutter, and other loss of control scenarios. In work conducted for NASA Dryden as part of a Phase II Small Business Innovation Research (SBIR) project, wavelet transform methods were developed for loss of control detection. The time varying frequency response identification methods were implemented and demonstrated in a real-time, flight control system hardware-in-the- loop, piloted simulation. This simulation included many of the realistic problems that are always part of test data, such as noise, multiple sample rates, and time skews. The variance of the identified frequency response was reduced using cross-spectra with smoothing in the time and frequency domain. Stability metrics were identified from the frequency response, including airplane bandwidth parameters, as they varied in time. The supporting software * Chief Scientist, AIAA Member.
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This note was uploaded on 01/10/2012 for the course AFGC-UF 4001 taught by Professor Fielding during the Spring '11 term at Hawaii Pacific.

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AIAA-2004-6838-498 - AIAA 2004-6838 USAF Developmental Test...

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