Dynamic modeling and fuzzy control for a small tiltrotor unmanned aerial vehicle-Reference-Cited by-同舟云学术

Dynamic modeling and fuzzy control for a small tiltrotor unmanned aerial vehicle

Published:2012-09-03 Issue:9 Volume:227 Page:1468-1487
ISSN:0954-4100
Container-title:Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
language:en
Short-container-title:Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering

Author:

Chang Sungho¹²,Bang Hyochoong¹,Lee Wonsuk¹,Park Bumjin²

Affiliation:

1. Division of Aerospace Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea

2. Korea Aerospace Research Institute, Republic of Korea

Abstract

Dynamic modeling and fuzzy control of a tiltrotor unmanned aerial vehicle are presented. In order to design a full-conversion flight controller for a tiltrotor unmanned aerial vehicle, the dynamic characteristics of a small tiltrotor unmanned aerial vehicle during helicopter-to-airplane conversion is investigated. A six-degree-of-freedom nonlinear equation of motion using powered wind tunnel test data is developed based on a Bell Model 301 tiltrotor research aircraft. The time-varying characteristics of the conversion maneuver, over which system dynamics change rapidly, are handled by a Takagi–Sugeno fuzzy control approach in both longitudinal and lateral axes. Simulation results indicate that a small tiltrotor unmanned aerial vehicle exhibits nacelle tilt during the backward conversion flight from airplane to helicopter mode.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Aerospace Engineering

Link

http://journals.sagepub.com/doi/pdf/10.1177/0954410012457620

Reference12 articles.

1. Development and Conversion Flight Test of a Small Tiltrotor Unmanned Aerial Vehicle

2. Trajectory tracking controller design using neural networks for a tiltrotor unmanned aerial vehicle

3. Fuzzy controllers as gain scheduling approximators

4. A fuzzy flight controller combining linguistic and model-based fuzzy control

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