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https://dspace.univ-ouargla.dz/jspui/handle/123456789/39450Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | khelifa, Moussa | - |
| dc.contributor.author | Benseghir, Asma | - |
| dc.contributor.author | Boulanouar, Aya | - |
| dc.date.accessioned | 2025-12-08T14:45:32Z | - |
| dc.date.available | 2025-12-08T14:45:32Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.uri | https://dspace.univ-ouargla.dz/jspui/handle/123456789/39450 | - |
| dc.description | Electrical Machines | en_US |
| dc.description.abstract | يتناول هذا المشروع تصميما وتطوير طائرة رباعية ذكية تهدف إلى تحسين الأداء الديناميكي للطيران باستخدام محاكاة برمجية في بيئة MATLAB.يتم اعتماد نماذج رياضية وخوارزميات تحكم مثل PID و PDلضمان الاستقرار وتتبع المسار بدقة عالية.كما تشمل الدراسة تحسين المعاملات باستخدام تقنيات مثل تحسين السرب الجزيئي(PSO).مما يساهم في تحسين الاستجابة ,تقليل الخطأ,وزيادة كفاءة النظام .يوفر هذا العمل أساسا مثينا لتطوير أنظمة طائرات بدون طيار أكثر ذكاء واعتمادية من خلال الدمج بين المحاكاة والتحليل الخوارزمي | en_US |
| dc.description.abstract | This project focuses on the design and development of an intelligent Quadcopter drone aimed at enhancing flight performance through MATLAB-based simulation. Mathematical modelling and control algorithms such as PID and PD are employed to ensure stability and accurate trajectory tracking. The study also integrates Particle Swarm Optimization (PSO) techniques to fine-tune control parameters, resulting in improved response time, reduced error, and greater system efficiency. This work provides a solid foundation for the development of smarter and more reliable unmanned aerial vehicles by combining simulation and algorithmic optimization. | - |
| dc.description.abstract | Ce projet porte sur la conception et le développement d’un drone quadri rotor intelligent, visant à améliorer les performances dynamiques du vol à l’aide d’une simulation logicielle dans l’environnement MATLAB. Des modèles mathématiques et des algorithmes de commande tels que PID et PD sont utilisés pour garantir la stabilité et un suivi précis de la trajectoire. L’étude inclut également l’optimisation des paramètres en utilisant des techniques comme l’optimisation par essaim de particules (PSO), ce qui contribue à améliorer la réponse du système, réduire l’erreur et augmenter son efficacité. Ce travail constitue une base solide pour le développement de systèmes de drones autonomes plus intelligents et plus fiables, en combinant la simulation numérique et l’optimisation algorithmique. | - |
| dc.language.iso | fr | en_US |
| dc.publisher | UNIVERSITÉ KASDI MERBAH – OUARGLA | en_US |
| dc.subject | systèmes embarqués intelligents | en_US |
| dc.subject | Drone quadri rotor intelligent | en_US |
| dc.subject | simulation MATLAB | en_US |
| dc.subject | optimisation des performances | en_US |
| dc.subject | algorithmes de commande | en_US |
| dc.subject | régulateur PID / PD | en_US |
| dc.subject | suivi de trajectoire | en_US |
| dc.subject | optimisation par essaim de particules (PSO) | en_US |
| dc.subject | véhicules aériens sans pilote (UAV) | en_US |
| dc.subject | stabilité de vol | en_US |
| dc.title | Design and optimization of a Quadrotor Drone control system using PD controller tuned by particle swarm optimization PSO in MATLAB | en_US |
| dc.type | Thesis | en_US |
| Appears in Collections: | Département de Génie électrique - Master | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Master_Finnal (aya+asma) (1).pdf | 3,98 MB | Adobe PDF | View/Open |
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