{"id":{"repo_id":"wvu","oai_identifier":"oai:researchrepository.wvu.edu:etd-1490"},"canonical_url":"https://search.dev.ndltd.org/etd/wvu/oai:researchrepository.wvu.edu:etd-1490","repository":{"repo_id":"wvu","name":"West Virginia University","base_url":"https://researchrepository.wvu.edu/do/oai/"},"display":{"title":"UAV Simulation Environment for Autonomous Flight Control Algorithms","abstract":"This thesis presents the development of a UAV simulation environment for the design, analysis, and comparison of autonomous flight control laws. The simulation environment was developed in MATLAB/Simulink, with custom map generation software and FlightGear 3-D visualization. Graphical user interface of the simulation environment is user-friendly and all available options are discussed in detail. Aircraft dynamic models are presented, with emphasis on newly designed UAV models. Five different aircraft models are available, with several path planning and trajectory tracking algorithms implemented. Emphasis is given to simulation of failures and other abnormal conditions, so that appropriate tools for failure detection, evaluation, and accommodation can be designed. The development of new path planning methodologies, such as optimized point of interest or automatic landing algorithms, is introduced. New developments in trajectory tracking algorithms, including adaptive controllers are discussed. An example simulation study is presented to investigate obstacle avoidance path planning algorithms, as well as the performance of trajectory tracking algorithms under both nominal and failure conditions. The results of this study are discussed with respect to optimum algorithm choice, as well as the user-friendliness of the UAV simulation environment as a whole. Finally, possible strategies for future improvements and expansion of the UAV simulation environment and its components are introduced.","abstract_html":"This thesis presents the development of a UAV simulation environment for the design, analysis, and comparison of autonomous flight control laws. The simulation environment was developed in MATLAB/Simulink, with custom map generation software and FlightGear 3-D visualization. Graphical user interface of the simulation environment is user-friendly and all available options are discussed in detail. Aircraft dynamic models are presented, with emphasis on newly designed UAV models. Five different aircraft models are available, with several path planning and trajectory tracking algorithms implemented. Emphasis is given to simulation of failures and other abnormal conditions, so that appropriate tools for failure detection, evaluation, and accommodation can be designed. The development of new path planning methodologies, such as optimized point of interest or automatic landing algorithms, is introduced. New developments in trajectory tracking algorithms, including adaptive controllers are discussed. An example simulation study is presented to investigate obstacle avoidance path planning algorithms, as well as the performance of trajectory tracking algorithms under both nominal and failure conditions. The results of this study are discussed with respect to optimum algorithm choice, as well as the user-friendliness of the UAV simulation environment as a whole. Finally, possible strategies for future improvements and expansion of the UAV simulation environment and its components are introduced.","abstract_has_math":false,"creators":["Karas, Ondrej"],"institution":null,"degree_name":"MS","degree_level":"Thesis","degree_discipline":"Mechanical and Aerospace Engineering","degree_department":null,"school":null,"contributors":["Mario Perhinschi","Peter Gall","Marcello Napolitano"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-05-01T07:00:00Z","date_published":"2012-05-01T07:00:00Z","updated_at":"2026-07-24T06:14:31Z","subjects":["Aerospace engineering","Artificial intelligence"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://researchrepository.wvu.edu/etd/487"],"render_values":[{"text":"https://researchrepository.wvu.edu/etd/487","href":"https://researchrepository.wvu.edu/etd/487","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.33915/etd.487","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mario Perhinschi","Peter Gall","Marcello Napolitano"]},{"key":"dc:creator","label":"Author","values":["Karas, Ondrej"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-10-29T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical and Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Aerospace engineering","Artificial intelligence"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.33915/etd.487","https://researchrepository.wvu.edu/etd/487"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis presents the development of a UAV simulation environment for the design, analysis, and comparison of autonomous flight control laws. The simulation environment was developed in MATLAB/Simulink, with custom map generation software and FlightGear 3-D visualization. Graphical user interface of the simulation environment is user-friendly and all available options are discussed in detail. Aircraft dynamic models are presented, with emphasis on newly designed UAV models. Five different aircraft models are available, with several path planning and trajectory tracking algorithms implemented. Emphasis is given to simulation of failures and other abnormal conditions, so that appropriate tools for failure detection, evaluation, and accommodation can be designed. The development of new path planning methodologies, such as optimized point of interest or automatic landing algorithms, is introduced. New developments in trajectory tracking algorithms, including adaptive controllers are discussed. An example simulation study is presented to investigate obstacle avoidance path planning algorithms, as well as the performance of trajectory tracking algorithms under both nominal and failure conditions. The results of this study are discussed with respect to optimum algorithm choice, as well as the user-friendliness of the UAV simulation environment as a whole. Finally, possible strategies for future improvements and expansion of the UAV simulation environment and its components are introduced."]},{"key":"dc:title","label":"Title","values":["UAV Simulation Environment for Autonomous Flight Control Algorithms"]}]}],"canonical_facts":{"dc:contributor":["Mario Perhinschi","Peter Gall","Marcello Napolitano"],"dc:creator":["Karas, Ondrej"],"dc:date.available":["2018-10-29T07:00:00Z"],"dc:description.abstract":["This thesis presents the development of a UAV simulation environment for the design, analysis, and comparison of autonomous flight control laws. The simulation environment was developed in MATLAB/Simulink, with custom map generation software and FlightGear 3-D visualization. Graphical user interface of the simulation environment is user-friendly and all available options are discussed in detail. Aircraft dynamic models are presented, with emphasis on newly designed UAV models. Five different aircraft models are available, with several path planning and trajectory tracking algorithms implemented. Emphasis is given to simulation of failures and other abnormal conditions, so that appropriate tools for failure detection, evaluation, and accommodation can be designed. The development of new path planning methodologies, such as optimized point of interest or automatic landing algorithms, is introduced. New developments in trajectory tracking algorithms, including adaptive controllers are discussed. An example simulation study is presented to investigate obstacle avoidance path planning algorithms, as well as the performance of trajectory tracking algorithms under both nominal and failure conditions. The results of this study are discussed with respect to optimum algorithm choice, as well as the user-friendliness of the UAV simulation environment as a whole. Finally, possible strategies for future improvements and expansion of the UAV simulation environment and its components are introduced."],"dc:identifier":["https://doi.org/10.33915/etd.487","https://researchrepository.wvu.edu/etd/487"],"dc:subject":["Aerospace engineering","Artificial intelligence"],"dc:title":["UAV Simulation Environment for Autonomous Flight Control Algorithms"],"thesis:degree_discipline":["Mechanical and Aerospace Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T06:14:31Z"}