Abstract
This paper presents the aerodynamics model of a small scale fixed-wing drone, the Multiplex Easyglider 4, together with the inner and outer loop control strategies to enable effective path following. The XFLR software is used to obtain the vehicle aerodynamic response based on a basic 3-D model of the fuselage and surfaces, towards having a complete dynamical model, including the aerodynamic coefficients. With this model, nonlinear control techniques are explored to deal with the aerodynamic nonlinearities and then integrated with a path following algorithm. Two types of attitude controllers were developed: A linear controller based on PI and a nonlinear controller based on the backstepping technique. An external loop was then added to make the vehicle follow a specific path. Two different techniques were implemented: A path following algorithm that would make the vehicle follow a vector field around the intended trajectory and an adaptive algorithm capable of dealing with uncertainties in the environment, such as wind with unknown direction and intensity. Simulation results are presented for each strategy and the instrumentation of the vehicle to be used in field trials is also provided.
Original language | English |
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Title of host publication | Proceedings |
Subtitle of host publication | 2023 International Young Engineers Forum in Electrical and Computer Engineering (YEF-ECE) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 71-77 |
Number of pages | 7 |
ISBN (Electronic) | 979-8-3503-0042-0 |
ISBN (Print) | 979-8-3503-0043-7 |
DOIs | |
Publication status | Published - 2023 |
Event | 2023 International Young Engineers Forum in Electrical and Computer Engineering - Caparica, Lisbon, Portugal Duration: 7 Jul 2023 → 7 Jul 2023 |
Conference
Conference | 2023 International Young Engineers Forum in Electrical and Computer Engineering |
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Abbreviated title | YEF-ECE 2023 |
Country/Territory | Portugal |
City | Lisbon |
Period | 7/07/23 → 7/07/23 |
Keywords
- Adaptive
- Backstepping
- Path following
- PID
- UAV
- Vector field