Modular systems have gained significant attention in various domains due to their flexibility, scalability, and adaptability. These systems consist of multiple interconnected modules that can be combined and reconfigured to achieve desired functionalities. The modular approach offers numerous advantages, including ease of maintenance, reduced downtime, and cost-effectiveness. However, designing effective distributed control strategies for modular systems presents unique challenges. Specifically, modular systems that consist of robot manipulators are subject to non-linear unknown terms as well as unknown effects. This thesis focuses on developing and designing a distributed model reference adaptive controller for a robotic modular system that is subject to non-linear unknown terms, robot-based uncertainties, as well as coupled dynamics. This thesis also provides extensive Lyapunov stability analysis and simulation results of the designed controller case by case. Specifically, control design of the modular system is shown in the absence of anomalies (i.e., non-linear unknown terms, robot-based uncertainties, and coupled dynamics) in Chapter 3, in the presence of non-linear unknown terms in Chapter 4, in the presence of non-linear unknown terms as well as robot-based uncertainties in Chapter 5, and in the presence of all anomalies in Chapter 6, respectively.
","abstract_html":"<p>Modular systems have gained significant attention in various domains due to their flexibility, scalability, and adaptability. These systems consist of multiple interconnected modules that can be combined and reconfigured to achieve desired functionalities. The modular approach offers numerous advantages, including ease of maintenance, reduced downtime, and cost-effectiveness. However, designing effective distributed control strategies for modular systems presents unique challenges. Specifically, modular systems that consist of robot manipulators are subject to non-linear unknown terms as well as unknown effects. This thesis focuses on developing and designing a distributed model reference adaptive controller for a robotic modular system that is subject to non-linear unknown terms, robot-based uncertainties, as well as coupled dynamics. This thesis also provides extensive Lyapunov stability analysis and simulation results of the designed controller case by case. Specifically, control design of the modular system is shown in the absence of anomalies (i.e., non-linear unknown terms, robot-based uncertainties, and coupled dynamics) in Chapter 3, in the presence of non-linear unknown terms in Chapter 4, in the presence of non-linear unknown terms as well as robot-based uncertainties in Chapter 5, and in the presence of all anomalies in Chapter 6, respectively.</p>","abstract_has_math":false,"creators":["Vongkunghae, Thitiphun"],"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":2023,"date_issued":"2023-08-01T07:00:00Z","date_published":"2023-08-01T07:00:00Z","updated_at":"2026-07-27T19:25:10Z","subjects":["\"distributed control\"","\"multiagent control\"","\"robotics\"","\"adaptive control\"","\"uncertain systems\"","Navigation, Guidance, Control and Dynamics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/763","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Vongkunghae, Thitiphun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2025-08-10T07:00:00Z"]},{"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":["\"distributed control\"","\"multiagent control\"","\"robotics\"","\"adaptive control\"","\"uncertain systems\"","Navigation, Guidance, Control and Dynamics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/763"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Modular systems have gained significant attention in various domains due to their flexibility, scalability, and adaptability. These systems consist of multiple interconnected modules that can be combined and reconfigured to achieve desired functionalities. The modular approach offers numerous advantages, including ease of maintenance, reduced downtime, and cost-effectiveness. However, designing effective distributed control strategies for modular systems presents unique challenges. Specifically, modular systems that consist of robot manipulators are subject to non-linear unknown terms as well as unknown effects. This thesis focuses on developing and designing a distributed model reference adaptive controller for a robotic modular system that is subject to non-linear unknown terms, robot-based uncertainties, as well as coupled dynamics. This thesis also provides extensive Lyapunov stability analysis and simulation results of the designed controller case by case. Specifically, control design of the modular system is shown in the absence of anomalies (i.e., non-linear unknown terms, robot-based uncertainties, and coupled dynamics) in Chapter 3, in the presence of non-linear unknown terms in Chapter 4, in the presence of non-linear unknown terms as well as robot-based uncertainties in Chapter 5, and in the presence of all anomalies in Chapter 6, respectively.
"]},{"key":"dc:title","label":"Title","values":["Multiple Uncertain Robot Manipulator Control for a Modular System"]}]}],"canonical_facts":{"dc:creator":["Vongkunghae, Thitiphun"],"dc:date.available":["2025-08-10T07:00:00Z"],"dc:description.abstract":["Modular systems have gained significant attention in various domains due to their flexibility, scalability, and adaptability. These systems consist of multiple interconnected modules that can be combined and reconfigured to achieve desired functionalities. The modular approach offers numerous advantages, including ease of maintenance, reduced downtime, and cost-effectiveness. However, designing effective distributed control strategies for modular systems presents unique challenges. Specifically, modular systems that consist of robot manipulators are subject to non-linear unknown terms as well as unknown effects. This thesis focuses on developing and designing a distributed model reference adaptive controller for a robotic modular system that is subject to non-linear unknown terms, robot-based uncertainties, as well as coupled dynamics. This thesis also provides extensive Lyapunov stability analysis and simulation results of the designed controller case by case. Specifically, control design of the modular system is shown in the absence of anomalies (i.e., non-linear unknown terms, robot-based uncertainties, and coupled dynamics) in Chapter 3, in the presence of non-linear unknown terms in Chapter 4, in the presence of non-linear unknown terms as well as robot-based uncertainties in Chapter 5, and in the presence of all anomalies in Chapter 6, respectively.
"],"dc:identifier":["https://commons.erau.edu/edt/763"],"dc:subject":["\"distributed control\"","\"multiagent control\"","\"robotics\"","\"adaptive control\"","\"uncertain systems\"","Navigation, Guidance, Control and Dynamics"],"dc:title":["Multiple Uncertain Robot Manipulator Control for a Modular System"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Aerospace Engineering"]},"updated_at":"2026-07-27T19:25:10Z"}