For a multiagent system, a major challenge is achieving overall system stability and performance in the presence of not only uncertainties but also coupled dynamics. Another challenge for these systems is designing distributed adaptive controllers with user-assigned positions in this case and defining the convergence rate of the reference model for each agent using only local (i.e., agent-based) information. Discrete-time architectures have an advantage over their continuous counterparts as they can be directly executed on embedded hardware without the need for discretization. Yet, because of the difficulty of ensuring Lyapunov difference expressions, their designs, which are based on quadratic Lyapunov-based frameworks, are highly complex. As a result, various existing continuous-time results using adaptive control methods to deal with system uncertainties and coupled dynamics in agents of a multiagent system cannot be directly applied to the discrete-time context as it can yield a loss of stability margins.
To this end, this dissertation presents novel model reference and distributed/decentralized adaptive control algorithms designed for scalar and high-order uncertain multiagent systems in the presence of coupled dynamics that allows for choosing user-assigned positions for each agent. Specifically, this work proposes continuous and discrete-time distributed adaptive approaches for multiagent systems in the presence of agent-based uncertainties, uncertainty in actuator effectiveness, and unmeasurable coupled dynamics. Moreover, these solutions offer flexibility in positioning agents in space without using global information by user-assigned Laplacian matrix nullspaces.
First, a literature review and motivation, followed by contribution, are given. Then, the problems are formulated for scalar and high-order multiagent systems, adaptive control designs along with the stability analyses are provided for continuous and discrete-time setting, and numerical and experimental examples are given to show efficacy of the proposed controllers. Finally, concluding remarks with potential research and published work are provided.
","abstract_html":"<p>For a multiagent system, a major challenge is achieving overall system stability and performance in the presence of not only uncertainties but also coupled dynamics. Another challenge for these systems is designing distributed adaptive controllers with user-assigned positions in this case and defining the convergence rate of the reference model for each agent using only local (i.e., agent-based) information. Discrete-time architectures have an advantage over their continuous counterparts as they can be directly executed on embedded hardware without the need for discretization. Yet, because of the difficulty of ensuring Lyapunov difference expressions, their designs, which are based on quadratic Lyapunov-based frameworks, are highly complex. As a result, various existing continuous-time results using adaptive control methods to deal with system uncertainties and coupled dynamics in agents of a multiagent system cannot be directly applied to the discrete-time context as it can yield a loss of stability margins.</p> <p>To this end, this dissertation presents novel model reference and distributed/decentralized adaptive control algorithms designed for scalar and high-order uncertain multiagent systems in the presence of coupled dynamics that allows for choosing user-assigned positions for each agent. Specifically, this work proposes continuous and discrete-time distributed adaptive approaches for multiagent systems in the presence of agent-based uncertainties, uncertainty in actuator effectiveness, and unmeasurable coupled dynamics. Moreover, these solutions offer flexibility in positioning agents in space without using global information by user-assigned Laplacian matrix nullspaces.</p> <p>First, a literature review and motivation, followed by contribution, are given. Then, the problems are formulated for scalar and high-order multiagent systems, adaptive control designs along with the stability analyses are provided for continuous and discrete-time setting, and numerical and experimental examples are given to show efficacy of the proposed controllers. Finally, concluding remarks with potential research and published work are provided.</p>","abstract_has_math":false,"creators":["Aly, Islam"],"institution":null,"degree_name":"Doctor of Philosophy in Aerospace Engineering","degree_level":"Dissertation - Open Access","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-04-01T07:00:00Z","date_published":"2024-04-01T07:00:00Z","updated_at":"2026-07-27T19:25:29Z","subjects":["Distributed Adaptive Control","Uncertain Multiagent Systems","Coupled Dynamics","Discrete-Time","Graph Theory","Navigation, Guidance, Control and Dynamics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/798","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Aly, Islam"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2026-03-19T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy in Aerospace Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Distributed Adaptive Control","Uncertain Multiagent Systems","Coupled Dynamics","Discrete-Time","Graph Theory","Navigation, Guidance, Control and Dynamics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/798"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["For a multiagent system, a major challenge is achieving overall system stability and performance in the presence of not only uncertainties but also coupled dynamics. Another challenge for these systems is designing distributed adaptive controllers with user-assigned positions in this case and defining the convergence rate of the reference model for each agent using only local (i.e., agent-based) information. Discrete-time architectures have an advantage over their continuous counterparts as they can be directly executed on embedded hardware without the need for discretization. Yet, because of the difficulty of ensuring Lyapunov difference expressions, their designs, which are based on quadratic Lyapunov-based frameworks, are highly complex. As a result, various existing continuous-time results using adaptive control methods to deal with system uncertainties and coupled dynamics in agents of a multiagent system cannot be directly applied to the discrete-time context as it can yield a loss of stability margins.
To this end, this dissertation presents novel model reference and distributed/decentralized adaptive control algorithms designed for scalar and high-order uncertain multiagent systems in the presence of coupled dynamics that allows for choosing user-assigned positions for each agent. Specifically, this work proposes continuous and discrete-time distributed adaptive approaches for multiagent systems in the presence of agent-based uncertainties, uncertainty in actuator effectiveness, and unmeasurable coupled dynamics. Moreover, these solutions offer flexibility in positioning agents in space without using global information by user-assigned Laplacian matrix nullspaces.
First, a literature review and motivation, followed by contribution, are given. Then, the problems are formulated for scalar and high-order multiagent systems, adaptive control designs along with the stability analyses are provided for continuous and discrete-time setting, and numerical and experimental examples are given to show efficacy of the proposed controllers. Finally, concluding remarks with potential research and published work are provided.
"]},{"key":"dc:title","label":"Title","values":["Distributed adaptive control methods for uncertain multiagent systems with coupled dynamics"]}]}],"canonical_facts":{"dc:creator":["Aly, Islam"],"dc:date.available":["2026-03-19T07:00:00Z"],"dc:description.abstract":["For a multiagent system, a major challenge is achieving overall system stability and performance in the presence of not only uncertainties but also coupled dynamics. Another challenge for these systems is designing distributed adaptive controllers with user-assigned positions in this case and defining the convergence rate of the reference model for each agent using only local (i.e., agent-based) information. Discrete-time architectures have an advantage over their continuous counterparts as they can be directly executed on embedded hardware without the need for discretization. Yet, because of the difficulty of ensuring Lyapunov difference expressions, their designs, which are based on quadratic Lyapunov-based frameworks, are highly complex. As a result, various existing continuous-time results using adaptive control methods to deal with system uncertainties and coupled dynamics in agents of a multiagent system cannot be directly applied to the discrete-time context as it can yield a loss of stability margins.
To this end, this dissertation presents novel model reference and distributed/decentralized adaptive control algorithms designed for scalar and high-order uncertain multiagent systems in the presence of coupled dynamics that allows for choosing user-assigned positions for each agent. Specifically, this work proposes continuous and discrete-time distributed adaptive approaches for multiagent systems in the presence of agent-based uncertainties, uncertainty in actuator effectiveness, and unmeasurable coupled dynamics. Moreover, these solutions offer flexibility in positioning agents in space without using global information by user-assigned Laplacian matrix nullspaces.
First, a literature review and motivation, followed by contribution, are given. Then, the problems are formulated for scalar and high-order multiagent systems, adaptive control designs along with the stability analyses are provided for continuous and discrete-time setting, and numerical and experimental examples are given to show efficacy of the proposed controllers. Finally, concluding remarks with potential research and published work are provided.
"],"dc:identifier":["https://commons.erau.edu/edt/798"],"dc:subject":["Distributed Adaptive Control","Uncertain Multiagent Systems","Coupled Dynamics","Discrete-Time","Graph Theory","Navigation, Guidance, Control and Dynamics"],"dc:title":["Distributed adaptive control methods for uncertain multiagent systems with coupled dynamics"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Dissertation - Open Access"],"thesis:degree_name":["Doctor of Philosophy in Aerospace Engineering"]},"updated_at":"2026-07-27T19:25:29Z"}