The thesis project proposes analytical and theoretical algorithms for a networked swarm of autonomous vehicles, such as those used in planet exploration, and to be used in target location determination and convergence, an algorithm of this type could be used in an Autonomous Stratospheric Aircraft (ASA), thus having the possibility of being used for the exploration of a planet as well as many other applications. Upon locating an unknown location of a specified target, the algorithm would then swarm and eventually converge upon the location. There are two similar, but fundamentally different algorithms proposed in this project. These algorithms are capable of locating and converging upon multiple targeted locations simultaneously. This project is inspired by the current thought of NASA in the search of life on Mars, which is the Water\" where the targeted location would be the targeted source of water. These algorithms make use of combining a modified Particle Swarm Optimization algorithm with fuzzy variables for increased intelligence.
","abstract_html":"<p>The thesis project proposes analytical and theoretical algorithms for a networked swarm of autonomous vehicles, such as those used in planet exploration, and to be used in target location determination and convergence, an algorithm of this type could be used in an Autonomous Stratospheric Aircraft (ASA), thus having the possibility of being used for the exploration of a planet as well as many other applications. Upon locating an unknown location of a specified target, the algorithm would then swarm and eventually converge upon the location. There are two similar, but fundamentally different algorithms proposed in this project. These algorithms are capable of locating and converging upon multiple targeted locations simultaneously. This project is inspired by the current thought of NASA in the search of life on Mars, which is the Water" where the targeted location would be the targeted source of water. These algorithms make use of combining a modified Particle Swarm Optimization algorithm with fuzzy variables for increased intelligence.</p>","abstract_has_math":false,"creators":["Richards, Zach D."],"institution":null,"degree_name":"M.S.","degree_level":"Masters Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Roger Salters, Ph.D.","Kimon Valavanis","Cynthia McRae"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-01-01T08:00:00Z","date_published":"2009-01-01T08:00:00Z","updated_at":"2026-07-24T02:02:11Z","subjects":["Autonomous convergence","Fuzzy theory","Particle swarm","Robotic control","Swarm theory","Target determination","Mechanical Engineering","Other Computer Engineering","Other Mechanical Engineering"],"languages":["en"],"rights":["Copyright is held by the author. User is responsible for all copyright compliance.
"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.du.edu/etd/549","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Roger Salters, Ph.D.","Kimon Valavanis","Cynthia McRae"]},{"key":"dc:creator","label":"Author","values":["Richards, Zach D."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2001-01-01T08:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Autonomous convergence","Fuzzy theory","Particle swarm","Robotic control","Swarm theory","Target determination","Mechanical Engineering","Other Computer Engineering","Other Mechanical Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright is held by the author. User is responsible for all copyright compliance.
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"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Fuzzy Optimal Swarm of Autonomous Aircrafts for Target Determination and Convergence Control System"]}]}],"canonical_facts":{"dc:contributor":["Roger Salters, Ph.D.","Kimon Valavanis","Cynthia McRae"],"dc:creator":["Richards, Zach D."],"dc:date.available":["2001-01-01T08:00:00Z"],"dc:description.abstract":["The thesis project proposes analytical and theoretical algorithms for a networked swarm of autonomous vehicles, such as those used in planet exploration, and to be used in target location determination and convergence, an algorithm of this type could be used in an Autonomous Stratospheric Aircraft (ASA), thus having the possibility of being used for the exploration of a planet as well as many other applications. Upon locating an unknown location of a specified target, the algorithm would then swarm and eventually converge upon the location. There are two similar, but fundamentally different algorithms proposed in this project. These algorithms are capable of locating and converging upon multiple targeted locations simultaneously. This project is inspired by the current thought of NASA in the search of life on Mars, which is the Water\" where the targeted location would be the targeted source of water. These algorithms make use of combining a modified Particle Swarm Optimization algorithm with fuzzy variables for increased intelligence.
"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/549"],"dc:language":["en"],"dc:rights":["Copyright is held by the author. User is responsible for all copyright compliance.
"],"dc:subject":["Autonomous convergence","Fuzzy theory","Particle swarm","Robotic control","Swarm theory","Target determination","Mechanical Engineering","Other Computer Engineering","Other Mechanical Engineering"],"dc:title":["Fuzzy Optimal Swarm of Autonomous Aircrafts for Target Determination and Convergence Control System"],"thesis:degree_level":["Masters Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T02:02:11Z"}