This thesis presents the system identification of the longitudinal motion of a small unmanned aerial vehicle with flexible characteristics. The unmanned aerial vehicle of study is an off-the-shelf aircraft with limited knowledge about the dynamic model. The first task in obtaining a model for flutter testing is determining the rigid body model. Specifically, this thesis will focus in the development of the aircraft and obtaining the longitudinal rigid body model. This involves the assembly and configuration of the avionics and sensors, performing experiments to determine mass and inertia properties and using software tools for aerodynamic analysis to get preliminary values for the static and dynamic stability derivatives. The next step was to design flight experiments for the purpose of system identification. The system identification focused on obtaining the longitudinal model and available software tools were used to get comparative results. The best model was identified using the parameter identification library which gave a 65% match in the pitch rate and 70% match in the vertical acceleration flight data from a doublet response. The short period mode was identified to have a frequency of 6.01 rad/s and a damping ratio of 0.977.
","abstract_html":"<p>This thesis presents the system identification of the longitudinal motion of a small unmanned aerial vehicle with flexible characteristics. The unmanned aerial vehicle of study is an off-the-shelf aircraft with limited knowledge about the dynamic model. The first task in obtaining a model for flutter testing is determining the rigid body model. Specifically, this thesis will focus in the development of the aircraft and obtaining the longitudinal rigid body model. This involves the assembly and configuration of the avionics and sensors, performing experiments to determine mass and inertia properties and using software tools for aerodynamic analysis to get preliminary values for the static and dynamic stability derivatives. The next step was to design flight experiments for the purpose of system identification. The system identification focused on obtaining the longitudinal model and available software tools were used to get comparative results. The best model was identified using the parameter identification library which gave a 65% match in the pitch rate and 70% match in the vertical acceleration flight data from a doublet response. The short period mode was identified to have a frequency of 6.01 rad/s and a damping ratio of 0.977.</p>","abstract_has_math":false,"creators":["Hamada, Said S."],"institution":null,"degree_name":"Master of Science in Aerospace Engineering","degree_level":"Thesis - Open Access","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-05-01T07:00:00Z","date_published":"2018-05-01T07:00:00Z","updated_at":"2026-07-27T19:25:37Z","subjects":["unmanned aerial vehicles","longitudinal","flutter","Aeronautical Vehicles"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/395","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Hamada, Said S."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Aerospace Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["unmanned aerial vehicles","longitudinal","flutter","Aeronautical Vehicles"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/395"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis presents the system identification of the longitudinal motion of a small unmanned aerial vehicle with flexible characteristics. The unmanned aerial vehicle of study is an off-the-shelf aircraft with limited knowledge about the dynamic model. The first task in obtaining a model for flutter testing is determining the rigid body model. Specifically, this thesis will focus in the development of the aircraft and obtaining the longitudinal rigid body model. This involves the assembly and configuration of the avionics and sensors, performing experiments to determine mass and inertia properties and using software tools for aerodynamic analysis to get preliminary values for the static and dynamic stability derivatives. The next step was to design flight experiments for the purpose of system identification. The system identification focused on obtaining the longitudinal model and available software tools were used to get comparative results. The best model was identified using the parameter identification library which gave a 65% match in the pitch rate and 70% match in the vertical acceleration flight data from a doublet response. The short period mode was identified to have a frequency of 6.01 rad/s and a damping ratio of 0.977.
"]},{"key":"dc:title","label":"Title","values":["Development of a Small Unmanned Aerial Vehicle Longitudinal Model for Future Flutter Testing"]}]}],"canonical_facts":{"dc:creator":["Hamada, Said S."],"dc:description.abstract":["This thesis presents the system identification of the longitudinal motion of a small unmanned aerial vehicle with flexible characteristics. The unmanned aerial vehicle of study is an off-the-shelf aircraft with limited knowledge about the dynamic model. The first task in obtaining a model for flutter testing is determining the rigid body model. Specifically, this thesis will focus in the development of the aircraft and obtaining the longitudinal rigid body model. This involves the assembly and configuration of the avionics and sensors, performing experiments to determine mass and inertia properties and using software tools for aerodynamic analysis to get preliminary values for the static and dynamic stability derivatives. The next step was to design flight experiments for the purpose of system identification. The system identification focused on obtaining the longitudinal model and available software tools were used to get comparative results. The best model was identified using the parameter identification library which gave a 65% match in the pitch rate and 70% match in the vertical acceleration flight data from a doublet response. The short period mode was identified to have a frequency of 6.01 rad/s and a damping ratio of 0.977.
"],"dc:identifier":["https://commons.erau.edu/edt/395"],"dc:subject":["unmanned aerial vehicles","longitudinal","flutter","Aeronautical Vehicles"],"dc:title":["Development of a Small Unmanned Aerial Vehicle Longitudinal Model for Future Flutter Testing"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Aerospace Engineering"]},"updated_at":"2026-07-27T19:25:37Z"}