| Titre : |
Icing Detection, State Estimation, and Control of Fixed-Wing Drones |
| Titre original : |
Détection de givrage, estimation d’état et commande de drones à voilure fixe |
| Type de document : |
document électronique |
| Auteurs : |
Bilel Boulassel, Auteur ; Ilyes Chaabeni, Auteur ; Mohamed Tadjine, Directeur de thèse ; Toufik Souanef, Directeur de thèse |
| Editeur : |
[S.l.] : [s.n.] |
| Année de publication : |
2025 |
| Importance : |
1 fichier PDF (17.7 Mo) |
| Présentation : |
ill. |
| Note générale : |
d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 139-146
Mémoire confidentiel 2ans jusqu'à Juin 2027 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Fixed
wing Unmanned Aerial Vehicle
Icing detection
Particle filter
Sliding Mode
Formation contro |
| Résumé : |
Reliable operation of unmanned aerial vehicles (UAVs) in uncertain and adverse conditions
remains a critical challenge, particularly in the presence of icing, disturbances, and dynamic interactions in multi-agent systems. This thesis develops an integrated framework that combines
probabilistic estimation and nonlinear control strategies to enhance performance and robustness. An approach based on the particle filter (PF) is employed to improve state estimation accuracy and detect icing-related faults by analyzing variations in system parameters. For robust
trajectory tracking in uncertain flight conditions, the proposed control scheme combines a high-order sliding mode observer (HOSMO) with the super-twisting algorithms (STA), effectively
managing disturbances and model variations. At the multi-agent level, a distributed control
strategy is introduced, utilizing finite-time observers and controllers within a leader–follower
structure to enable fast and coordinated group behavior. The thesis demonstrates the effectiveness of the proposed methods in enhancing fault detection capabilities, control robustness,
and ensuring reliable multi-UAV coordination |
Icing Detection, State Estimation, and Control of Fixed-Wing Drones = Détection de givrage, estimation d’état et commande de drones à voilure fixe [document électronique] / Bilel Boulassel, Auteur ; Ilyes Chaabeni, Auteur ; Mohamed Tadjine, Directeur de thèse ; Toufik Souanef, Directeur de thèse . - [S.l.] : [s.n.], 2025 . - 1 fichier PDF (17.7 Mo) : ill. d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 139-146
Mémoire confidentiel 2ans jusqu'à Juin 2027 Langues : Anglais ( eng)
| Mots-clés : |
Fixed
wing Unmanned Aerial Vehicle
Icing detection
Particle filter
Sliding Mode
Formation contro |
| Résumé : |
Reliable operation of unmanned aerial vehicles (UAVs) in uncertain and adverse conditions
remains a critical challenge, particularly in the presence of icing, disturbances, and dynamic interactions in multi-agent systems. This thesis develops an integrated framework that combines
probabilistic estimation and nonlinear control strategies to enhance performance and robustness. An approach based on the particle filter (PF) is employed to improve state estimation accuracy and detect icing-related faults by analyzing variations in system parameters. For robust
trajectory tracking in uncertain flight conditions, the proposed control scheme combines a high-order sliding mode observer (HOSMO) with the super-twisting algorithms (STA), effectively
managing disturbances and model variations. At the multi-agent level, a distributed control
strategy is introduced, utilizing finite-time observers and controllers within a leader–follower
structure to enable fast and coordinated group behavior. The thesis demonstrates the effectiveness of the proposed methods in enhancing fault detection capabilities, control robustness,
and ensuring reliable multi-UAV coordination |
|
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