Direct Inverse Control using an Artificial Neural Network for the Autonomous Hover of a Helicopter

Abstract

This paper presents the initial results of a research project which investigates the application of the Direct Inverse Control technique to the problem of the Autonomous Hover of a quadrotor UAV Helicopter. The goal of the project is to investigate the effectiveness of the Direct Inverse Control technique using an Artificial Neural Network to learn and then cancel out the Hover dynamics of the quadrotor UAV Helicopter under various environmental conditions during a hover mode. The project is to evaluate how robust the control technique is to uncertainty and change in nonlinear dynamics.

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Document Details

Document Type
Technical Report
Publication Date
Oct 05, 2014
Accession Number
ADA618593

Entities

People

  • Michael T. Frye
  • Robert S. Provence

Organizations

  • University of the Incarnate Word

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Autonomous Guidance
  • Autonomous Vehicles
  • Control Systems
  • Control Theory
  • Dynamics
  • Engineering
  • Flight Testing
  • Frequency Response
  • Helicopters
  • Navigation
  • Neural Networks
  • Nonlinear Dynamics
  • Rotary Wing Aircraft
  • Simulations
  • Transfer Functions
  • Vehicles

Readers

  • Aviation Science / Aeronautics.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks