Thrust-Induced Effects on a Pitching-Up Delta Wing Flow Field: Control of Stalled Wings

Abstract

Neural network procedures were explored with the objectives to control a delta wing in the non-linear domain. Results show that neural networks are well suited to represent non-linear computed lift and pressure forces on delta wings. A model problem, the flare maneuver, suggests that neural network controllers can perform well for non-linear systems provided that suitable input and training data are provided to it.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Nov 22, 1995
Accession Number
ADA329654

Entities

People

  • L. Van Dommelen

Organizations

  • Florida State University

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force
  • Coefficients
  • Computer Programs
  • Curve Fitting
  • Delta Wings
  • Engineering
  • Flow
  • Flow Fields
  • Graphical User Interface
  • Linear Systems
  • Maneuvers
  • Mechanical Engineering
  • Neural Networks
  • Simulators
  • Standards
  • Training
  • User Interface

Readers

  • Aerodynamics/Aeronautics.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks