Adaptive Neuro-Fuzzy Modeling of UH-60A Pilot Vibration

Abstract

Adaptive neuro-fuzzy relationships have been developed to model the UH-60A Black Hawk pilot floor vertical vibration. A 200 point database that approximates the entire UH-60A helicopter flight envelope is used for training and testing purposes. The NASA/Army Airloads Program flight test database was the source of the 200 point database. The present study is conducted in two parts. The first part involves level flight conditions and the second part involves the entire (200 point) database including maneuver conditions. The results show that a neuro-fuzzy model can successfully predict the pilot vibration. Also, it is found that the training phase of this neuro-fuzzy model takes only two or three iterations to converge for most cases. Thus the proposed approach produces a potentially viable model for real-time implementation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA532493

Entities

People

  • Heidar A. Malki
  • Reza Langari
  • Sesi Kottapalli

Organizations

  • National Aeronautics and Space Administration

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aeronautics
  • Aircrafts
  • Astronautics
  • Data Sets
  • Databases
  • Errors
  • Flight
  • Fuzzy Logic
  • Helicopters
  • Level Flight
  • Logic
  • Maneuvers
  • Neural Networks
  • Rotary Wing Aircraft
  • Tilt Rotor Aircraft
  • Training
  • Vibration

Readers

  • Aerospace Engineering
  • Computational Modeling and Simulation
  • Human-Computer Interaction (HCI).