Identification of Multivariable Gas Turbine Dynamics from Stochastic Input-Output Data.

Abstract

Results directed toward the identification of multivariable gas turbine engine dynamics from stochastic input-output data are described. An identification algorithm based on modern state estimation theory was developed to identify the parameters of a linear time-invariant F100/F401 turbofan engine model. Unknown parameters of the F100/F401 model were introduced as auxiliary state variables thereby transforming the parameter identification problem to a nonlinear state estimation problem. The engine model was forced by commanded changes in main burner fuel flow and jet exhaust area. Gaussian noise was added to the commanded fuel flow to model metering valve uncertainties. Noise-corrupted measurements consisted of fan turbine inlet temperature, fan and compressor speeds, and main burner and afterburner pressures. The identification procedure was carried out at three steady-state design points between idle and military conditions.

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1975
Accession Number
ADA006277

Entities

People

  • Florence A. Farrar
  • Gerald J. Michael

Tags

DTIC Thesaurus Topics

  • Afterburners
  • Dynamics
  • Engines
  • Gas Turbine Regenerators
  • Gas Turbines
  • Gaussian Noise
  • Identification
  • Jet Engines
  • Measurement
  • Noise
  • Steady State
  • Turbine Components
  • Turbines
  • Turbofan Engines

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerospace Engineering
  • Internal Combustion Engine (ICE) Technology.