Envelope Protection for Autonomous Unmanned Aerial Vehicles

This paper describes the design, development, and testing of an automatic envelope protection system as implemented on Georgia Institute of Technology's unmanned helicopter GTMax. The envelope protection system makes use of online-learning adaptive neural networks to generate online dynamic mod...

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Bibliographic Details
Published in:Journal of guidance, control, and dynamics control, and dynamics, 2009-01, Vol.32 (1), p.248-261
Main Authors: Yavrucuk, Ilkay, Unnikrishnan, Suraj, Prasad, J.V.R
Format: Article
Language:English
Subjects:
Aerospace engineering
Aircraft
Applied sciences
Computer science
control theory
systems
Control algorithms
Control theory. Systems
Controllers
Exact sciences and technology
Load
Neural networks
Robotics
Unmanned aerial vehicles
Vehicles
Workloads
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Summary:This paper describes the design, development, and testing of an automatic envelope protection system as implemented on Georgia Institute of Technology's unmanned helicopter GTMax. The envelope protection system makes use of online-learning adaptive neural networks to generate online dynamic models, which are used to estimate limits on controller commands. The system provides command capability up to the limit boundaries while preventing envelope exceedance. Simulation and flight-test results are provided for load factor and rotor stall limit protection during aggressive maneuvering. [PUBLISHER ABSTRACT]
ISSN:0731-5090
1533-3884
DOI:10.2514/1.35265