{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/140816"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/140816","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Performance and Robustness Assessment for a Robust Port-Hamiltonian Flight Controller","abstract":"Those conducting research in the field of nonlinear control of unmanned air vehicles are constantly searching to improve robustness and performance of flight control systems through new control laws. A control law can be designed to provide robustness guarantees due to the structure of the aircraft dynamics. This work presents an implementation of a novel control law which simultaneously transforms the nonlinear fixed-wing aircraft dynamics into a port-Hamiltonian structure using feedback linearization, from which input-to-state stability guarantees follow. This novel control law is compared to two industry standard methods, linear quadratic regulator and nonlinear dynamic inversion, which provide a baseline for comparing robustness and performance. To replicate flight, measurement noise, model mismatch, wind, and discretization with time delay were implemented in a collection of simulation studies to understand which disturbances the novel control law was most sensitive to. Due to the non-additive nature and magnitude of the applied disturbances, the novel control law was most sensitive to combinations of disturbances of wind, discretization with time delay, model mismatch, and measurement noise in order of greatest to least sensitivity. The novel control law performed as expected, and much better than both competitors, when the disturbances applied did not include wind. This result was due to a particular interaction between the wind disturbance and the construction of the novel control law that was not present with other disturbances. Future work includes flight testing and extending the robustness guarantees to non-feedback linearized systems.","abstract_html":"Those conducting research in the field of nonlinear control of unmanned air vehicles are constantly searching to improve robustness and performance of flight control systems through new control laws. A control law can be designed to provide robustness guarantees due to the structure of the aircraft dynamics. This work presents an implementation of a novel control law which simultaneously transforms the nonlinear fixed-wing aircraft dynamics into a port-Hamiltonian structure using feedback linearization, from which input-to-state stability guarantees follow. This novel control law is compared to two industry standard methods, linear quadratic regulator and nonlinear dynamic inversion, which provide a baseline for comparing robustness and performance. To replicate flight, measurement noise, model mismatch, wind, and discretization with time delay were implemented in a collection of simulation studies to understand which disturbances the novel control law was most sensitive to. Due to the non-additive nature and magnitude of the applied disturbances, the novel control law was most sensitive to combinations of disturbances of wind, discretization with time delay, model mismatch, and measurement noise in order of greatest to least sensitivity. The novel control law performed as expected, and much better than both competitors, when the disturbances applied did not include wind. This result was due to a particular interaction between the wind disturbance and the construction of the novel control law that was not present with other disturbances. Future work includes flight testing and extending the robustness guarantees to non-feedback linearized systems.","abstract_has_math":false,"creators":["Widman, Samuel"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Aerospace Engineering","degree_department":"Aerospace and Ocean Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Woolsey, Craig A."],"committee_members":["Psiaki, Mark L.","L'Afflitto, Andrea"],"year":2026,"date_issued":"2026-01-14","date_published":"2026-01-14","updated_at":"2026-07-22T22:20:16Z","subjects":["Flight Control","Robustness","Simulation","Port-Hamiltonian","Feedback Linearization"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:45194"],"render_values":[{"text":"vt_gsexam:45194","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/140816","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Woolsey, Craig A."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Psiaki, Mark L.","L'Afflitto, Andrea"]},{"key":"dc:contributor.department","label":"Department","values":["Aerospace and Ocean Engineering"]},{"key":"dc:creator","label":"Author","values":["Widman, Samuel"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-01-15T09:01:24Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-01-15T09:01:24Z"]},{"key":"dc:date.issued","label":"Date","values":["2026-01-14"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Flight Control","Robustness","Simulation","Port-Hamiltonian","Feedback Linearization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:45194"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/140816"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Those conducting research in the field of nonlinear control of unmanned air vehicles are constantly searching to improve robustness and performance of flight control systems through new control laws. A control law can be designed to provide robustness guarantees due to the structure of the aircraft dynamics. This work presents an implementation of a novel control law which simultaneously transforms the nonlinear fixed-wing aircraft dynamics into a port-Hamiltonian structure using feedback linearization, from which input-to-state stability guarantees follow. This novel control law is compared to two industry standard methods, linear quadratic regulator and nonlinear dynamic inversion, which provide a baseline for comparing robustness and performance. To replicate flight, measurement noise, model mismatch, wind, and discretization with time delay were implemented in a collection of simulation studies to understand which disturbances the novel control law was most sensitive to. Due to the non-additive nature and magnitude of the applied disturbances, the novel control law was most sensitive to combinations of disturbances of wind, discretization with time delay, model mismatch, and measurement noise in order of greatest to least sensitivity. The novel control law performed as expected, and much better than both competitors, when the disturbances applied did not include wind. This result was due to a particular interaction between the wind disturbance and the construction of the novel control law that was not present with other disturbances. Future work includes flight testing and extending the robustness guarantees to non-feedback linearized systems."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["A control law is a mathematical rule used to cause a physical system to follow a user-defined reference input. Many control laws exist for different systems, and each control law has inherent properties that make it better or worse for a given application. Two metrics used to determine if a control law is effective are tracking performance and robustness. Tracking performance is a measure of how closely a control law can follow a user-defined reference input, while robustness is a measure of how much a system can be disturbed from a nominal condition without significant degradation of performance. This work presents the implementation and analysis of a new control law applied to an unmanned aerial vehicle that is designed to provide a high level of tracking performance and robustness guarantees that ensure tracking performance degrades gracefully under the effect of disturbances. The new control law is compared to two other industry standard control laws in terms of both performance and robustness onboard a computer-simulated aircraft. A variety of realistic disturbances are applied to the aircraft, and the results demonstrate that the new control law is robust to certain disturbances and not to others."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Performance and Robustness Assessment for a Robust Port-Hamiltonian Flight Controller"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Woolsey, Craig A."],"dc:contributor.committeemember":["Psiaki, Mark L.","L'Afflitto, Andrea"],"dc:contributor.department":["Aerospace and Ocean Engineering"],"dc:creator":["Widman, Samuel"],"dc:date.accessioned":["2026-01-15T09:01:24Z"],"dc:date.available":["2026-01-15T09:01:24Z"],"dc:date.issued":["2026-01-14"],"dc:description.abstract":["Those conducting research in the field of nonlinear control of unmanned air vehicles are constantly searching to improve robustness and performance of flight control systems through new control laws. A control law can be designed to provide robustness guarantees due to the structure of the aircraft dynamics. This work presents an implementation of a novel control law which simultaneously transforms the nonlinear fixed-wing aircraft dynamics into a port-Hamiltonian structure using feedback linearization, from which input-to-state stability guarantees follow. This novel control law is compared to two industry standard methods, linear quadratic regulator and nonlinear dynamic inversion, which provide a baseline for comparing robustness and performance. To replicate flight, measurement noise, model mismatch, wind, and discretization with time delay were implemented in a collection of simulation studies to understand which disturbances the novel control law was most sensitive to. Due to the non-additive nature and magnitude of the applied disturbances, the novel control law was most sensitive to combinations of disturbances of wind, discretization with time delay, model mismatch, and measurement noise in order of greatest to least sensitivity. The novel control law performed as expected, and much better than both competitors, when the disturbances applied did not include wind. This result was due to a particular interaction between the wind disturbance and the construction of the novel control law that was not present with other disturbances. Future work includes flight testing and extending the robustness guarantees to non-feedback linearized systems."],"dc:description.abstractgeneral":["A control law is a mathematical rule used to cause a physical system to follow a user-defined reference input. Many control laws exist for different systems, and each control law has inherent properties that make it better or worse for a given application. Two metrics used to determine if a control law is effective are tracking performance and robustness. Tracking performance is a measure of how closely a control law can follow a user-defined reference input, while robustness is a measure of how much a system can be disturbed from a nominal condition without significant degradation of performance. This work presents the implementation and analysis of a new control law applied to an unmanned aerial vehicle that is designed to provide a high level of tracking performance and robustness guarantees that ensure tracking performance degrades gracefully under the effect of disturbances. The new control law is compared to two other industry standard control laws in terms of both performance and robustness onboard a computer-simulated aircraft. A variety of realistic disturbances are applied to the aircraft, and the results demonstrate that the new control law is robust to certain disturbances and not to others."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:45194"],"dc:identifier.uri":["https://hdl.handle.net/10919/140816"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Flight Control","Robustness","Simulation","Port-Hamiltonian","Feedback Linearization"],"dc:title":["Performance and Robustness Assessment for a Robust Port-Hamiltonian Flight Controller"],"dc:type":["Thesis"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:16Z"}