Neural Network Model of Unsteady, Nonlinear Aerodynamics

Author

Amy Pearsall Henderson, University of Tennessee - Knoxville

Date of Award

5-2002

Degree Type

Thesis

Degree Name

Master of Science

Major

Aerospace Engineering

Major Professor

Frank G. Collins

Committee Members

Kenneth K. Kimble, Bruce Whitehead

Abstract

Many flight control systems are developed from aerodynamic measurements obtained from static wind tunnel testing. These control systems frequently inadequately handle unsteady, nonlinear flight conditions. Dynamic roll angle measurements made in a wind tunnel have been obtained. This aerodynamic data presents a nonlinear, unsteady dynamical system. The roll angle trajectories have been successfully approximated with multilayer feedforward backpropagation neural networks.

Recommended Citation

Henderson, Amy Pearsall, "Neural Network Model of Unsteady, Nonlinear Aerodynamics. " Master's Thesis, University of Tennessee, 2002.
https://trace.tennessee.edu/utk_gradthes/2065