A master thesis from Aalborg University
Real time NMPC for fixed wing UAV applications: - Auto descent NMPC implementation on an embedded device -
[Real time NMPC for fixed wing UAV applications]
Author(s)
Term
4. term
Education
Publication year
2016
Submitted on
2016-06-06
Pages
85 pages
Abstract
Fix wing Unmanned Aerial Vehicles require a high degree of operational flexibility. There are numerous application that require the UAV to land in a limited space location. Fix wing UAV deep stall auto descent anding method is a way to perform such landing maneuver. However, a sophisticated precise control algorithm has to be implemented. This can be accomplished by expressing the maneuver as an Optimal Control Problem, taking advantage of the non-linear mathematical model acting on the fix wing UAV during flight. The Optimal Control Problem is solved in an open source optimization framework called ACADO Toolkit. Furthermore, the implementation of a nonlinear Model Predictive Control (NMPC) can drive the UAV running on embedded device. The purpose of this thesis is to present the process of implementing a real-time NMPC algorithm on an embedded device.
Keywords
fixed wing UAV ; NMPC ; ACADO ; OCP ; Numerical optimization ; Real time
Documents
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