Control Strategies for Autonomous Navigation Gun Launched Micro Aerial Vehicle

Nowadays, the use of rotary-wing MAV for observation missions in hostile environments is constantly growing. These aircrafts, through their ability to perform both translation fl ights and hover, are indeed well appropriate for these missions. The study presented in this thesis deals with a new MAV concept called GLMAV (for Gun Launched Micro Aerial Vehicle), which consists in getting very quickly up and running a projectile - MAV hybrid vehicle. The di fficulty in controlling such vehicles is to ensure good trajectory tracking performances while guaranteeing robustness towards aerodynamic disturbances. After a modelling stage, the heart of the thesis introduces various control strategies, both linear and nonlinear, for the autonomous navigation of the MAV. Several approaches allowing the estimation and the consideration into the control of the parasitic eff orts caused by aerodynamic phenomena are also detailed. The eff ectiveness of the control algorithms is then shown through many numerical simulations. From a practical point of view, having a control law is not enough. Indeed, special filtering techniques or specifi c equipments have to be used to reconstruct the system state. The performances of the overall control loop are fi rstly tested in simulation before its implementation on the GLMAV prototype developed by the French-German research Institute of Saint-Louis.

Data and Resources

Additional Info

Field Value
Source https://theses.hal.science/tel-01750350
Author Drouot, Adrien
Maintainer CCSD
Last Updated May 7, 2026, 17:11 (UTC)
Created May 7, 2026, 17:11 (UTC)
Identifier NNT: 2013LORR0172
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Centre de Recherche en Automatique de Nancy (CRAN) ; Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
creator Drouot, Adrien
date 2013-12-02T00:00:00
harvest_object_id aa8bd1f4-1e37-4cea-b331-23e851320981
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-11-04T00:00:00
set_spec type:THESE