A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone
This research focuses on modeling one of the Quadplane flight phases: a hover state, similar to a regular Quadcopter hovering. The process is highly non-linear, and additionally, there are more phenomena to take into account - it is related to air turbulence around the wings and the fuselage. This w...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9323029/ |
| _version_ | 1818351924806680576 |
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| author | Micha Okulski And Maciej Lawrynczuk |
| author_facet | Micha Okulski And Maciej Lawrynczuk |
| author_sort | Micha Okulski And |
| collection | DOAJ |
| description | This research focuses on modeling one of the Quadplane flight phases: a hover state, similar to a regular Quadcopter hovering. The process is highly non-linear, and additionally, there are more phenomena to take into account - it is related to air turbulence around the wings and the fuselage. This work thoroughly studies the effectiveness of various types of neural networks to model the drone using the data recorded from real free-flight experiments. Finally, we introduce a novel type of neural-based model: the Feature-Sequence-To-Sequence (fseq2seq) Recurrent Neural Network Model. The new Model has interesting features: the input-data-driven initialization of RNN's internal states and a simplification of the input layer (significant reduction of used neurons' weights). We demonstrate that the new network outperforms all classic model types. |
| first_indexed | 2024-12-13T18:45:28Z |
| format | Article |
| id | doaj.art-f6a0205579c2430789a8a254e1d86ae4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T18:45:28Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f6a0205579c2430789a8a254e1d86ae42022-12-21T23:35:06ZengIEEEIEEE Access2169-35362021-01-019141591417810.1109/ACCESS.2021.30518789323029A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane DroneMicha Okulski And0https://orcid.org/0000-0002-8481-9798Maciej Lawrynczuk1https://orcid.org/0000-0002-6846-2004Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, PolandInstitute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, PolandThis research focuses on modeling one of the Quadplane flight phases: a hover state, similar to a regular Quadcopter hovering. The process is highly non-linear, and additionally, there are more phenomena to take into account - it is related to air turbulence around the wings and the fuselage. This work thoroughly studies the effectiveness of various types of neural networks to model the drone using the data recorded from real free-flight experiments. Finally, we introduce a novel type of neural-based model: the Feature-Sequence-To-Sequence (fseq2seq) Recurrent Neural Network Model. The new Model has interesting features: the input-data-driven initialization of RNN's internal states and a simplification of the input layer (significant reduction of used neurons' weights). We demonstrate that the new network outperforms all classic model types.https://ieeexplore.ieee.org/document/9323029/Droneneural modelneural networkquadplanequad-planerecurrent neural network |
| spellingShingle | Micha Okulski And Maciej Lawrynczuk A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone IEEE Access Drone neural model neural network quadplane quad-plane recurrent neural network |
| title | A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone |
| title_full | A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone |
| title_fullStr | A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone |
| title_full_unstemmed | A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone |
| title_short | A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone |
| title_sort | novel neural network model applied to modeling of a tandem wing quadplane drone |
| topic | Drone neural model neural network quadplane quad-plane recurrent neural network |
| url | https://ieeexplore.ieee.org/document/9323029/ |
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