Flight Dynamics and Control of UAS-S4 and S45
Notice bibliographique
Résumé
In this paper, new methodologies are presented for flight dynamics and control model of two unmanned aerial systems (UAS) designed and developed in Mexico by Hydra Technologies. These two UAS are the UAS-S4 and UAS-S45. In fact, the aerodynamic model was developed by calculating the aerodynamic coefficients (lift, drag and pitching moment) using four various methods and their corresponding software. Two of these numerical methodologies are based on experimental data, therefore are semi-empirical, and programmed in two codes: the well-known DATCOM (developed by the US Air Force Flight Laboratories) and FDerivatives, that was developed by our team at the Laboratory of Active Controls, Avionics and AeroServoElasticity LARCASE. In both semi-empirical methodologies, the main geometrical characteristics of the wing, wing-body and all aircraft components are given as inputs to the two software, which gives as outputs the aerodynamic coefficients with their corresponding stability and control derivatives for various flight conditions. A third methodology is programmed using a low fidelity aerodynamics code called Tornado, which uses the Vortex Lattice Method (VLM). A fourth methodology is programmed using a high-fidelity aerodynamics code called Fluent in Ansys. This methodology used the Navier-Stokes equations. Therefore, a comparison is presented between the aerodynamic coefficients for a range of various flight cases, obtained using the three low-fidelity codes (DATCOM, FDerivatives and Tornado) and the ANSYS-FLUENT code. As the results were found to be close, it was considered that the estimation of the aerodynamic model was accurate. Then, this aerodynamic model was combined with the propulsion, structures and actuators models with the aim to develop a global flight dynamics model for each of the UAS. Then, a new controller methodology was performed with four combined theories: the Linear Quadratic Regulator (LQR), the Proportional Integral with reference feedforward (PI-FF), the Generalized Extended State Observer (GESO) as well as the Gain Scheduling based on the ANFIS-Fluent method. Based on these new methodologies and their findings, an excellent global flight dynamics and controller model were developed and resulted in the development of an excellent flight simulator model for both UAS-S4 and UAS-S45. This simulator model could be further generalized for other Unmanned Aerial Systems for their successful design and development.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».