{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/141061"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/141061","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Aircraft System Identification Approach for Control Surface Fault Diagnosis","abstract":"Modern fault detection and diagnosis (FDD) methods are critical to maintaining flight vehicle safety. This thesis presents a model-based FDD approach for identifying control-surface loss of effectiveness on a small, fixed-wing research aircraft. The work considers several real-time system identification methods to estimate changes in control effectiveness and provide fault information to a fault-tolerant control allocation framework. A baseline aero-propulsive model for an experimental aircraft was developed from flight-test data to establish nominal control-effectiveness parameters used to compare fault diagnosis methods. Five real-time estimation methods were formulated and evaluated: exponentially weighted recursive least squares in the time- and frequency-domain, two Lyapunov-based adaptive parameter estimation methods with exponential or finite-time convergence guarantees under a persistence of excitation condition, and an augmented-state extended Kalman filter. These methods were applied to flight data containing an artificially injected stuck left-aileron fault, implemented through a custom maneuver injection capability, with multisine excitation inputs applied to the control effectors. The estimated control-effectiveness parameters associated with the faulted surface displayed an immediate response to the failure and a clear trend towards zero, while the parameters corresponding to healthy effectors remained near nominal values. The resulting estimates were used to construct a time-varying health matrix that scales the nominal control-effectiveness matrix, producing a fault-weighted representation suitable for control allocation and supporting the objective of fault hiding. Overall, this work advances in-flight fault diagnosis by providing real-time parameter estimation for fault-tolerant control allocation, enabling redistribution of control authority to support flight operations.","abstract_html":"Modern fault detection and diagnosis (FDD) methods are critical to maintaining flight vehicle safety. This thesis presents a model-based FDD approach for identifying control-surface loss of effectiveness on a small, fixed-wing research aircraft. The work considers several real-time system identification methods to estimate changes in control effectiveness and provide fault information to a fault-tolerant control allocation framework. A baseline aero-propulsive model for an experimental aircraft was developed from flight-test data to establish nominal control-effectiveness parameters used to compare fault diagnosis methods. Five real-time estimation methods were formulated and evaluated: exponentially weighted recursive least squares in the time- and frequency-domain, two Lyapunov-based adaptive parameter estimation methods with exponential or finite-time convergence guarantees under a persistence of excitation condition, and an augmented-state extended Kalman filter. These methods were applied to flight data containing an artificially injected stuck left-aileron fault, implemented through a custom maneuver injection capability, with multisine excitation inputs applied to the control effectors. The estimated control-effectiveness parameters associated with the faulted surface displayed an immediate response to the failure and a clear trend towards zero, while the parameters corresponding to healthy effectors remained near nominal values. The resulting estimates were used to construct a time-varying health matrix that scales the nominal control-effectiveness matrix, producing a fault-weighted representation suitable for control allocation and supporting the objective of fault hiding. Overall, this work advances in-flight fault diagnosis by providing real-time parameter estimation for fault-tolerant control allocation, enabling redistribution of control authority to support flight operations.","abstract_has_math":false,"creators":["Corrigan, Patrick Edward"],"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.","Simmons, Benjamin Mason"],"committee_members":["Atkins, Ella"],"year":2026,"date_issued":"2026-01-29","date_published":"2026-01-29","updated_at":"2026-07-22T22:19:16Z","subjects":["Aircraft Modeling","Flight Test","Real-Time Parameter Estimation","Fault Detection and Diagnosis"],"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:45602"],"render_values":[{"text":"vt_gsexam:45602","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/141061","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.","Simmons, Benjamin Mason"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Atkins, Ella"]},{"key":"dc:contributor.department","label":"Department","values":["Aerospace and Ocean Engineering"]},{"key":"dc:creator","label":"Author","values":["Corrigan, Patrick Edward"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-01-30T09:00:24Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-01-30T09:00:24Z"]},{"key":"dc:date.issued","label":"Date","values":["2026-01-29"]},{"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":["Aircraft Modeling","Flight Test","Real-Time Parameter Estimation","Fault Detection and Diagnosis"]}]},{"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:45602"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/141061"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Modern fault detection and diagnosis (FDD) methods are critical to maintaining flight vehicle safety. This thesis presents a model-based FDD approach for identifying control-surface loss of effectiveness on a small, fixed-wing research aircraft. The work considers several real-time system identification methods to estimate changes in control effectiveness and provide fault information to a fault-tolerant control allocation framework. A baseline aero-propulsive model for an experimental aircraft was developed from flight-test data to establish nominal control-effectiveness parameters used to compare fault diagnosis methods. Five real-time estimation methods were formulated and evaluated: exponentially weighted recursive least squares in the time- and frequency-domain, two Lyapunov-based adaptive parameter estimation methods with exponential or finite-time convergence guarantees under a persistence of excitation condition, and an augmented-state extended Kalman filter. These methods were applied to flight data containing an artificially injected stuck left-aileron fault, implemented through a custom maneuver injection capability, with multisine excitation inputs applied to the control effectors. The estimated control-effectiveness parameters associated with the faulted surface displayed an immediate response to the failure and a clear trend towards zero, while the parameters corresponding to healthy effectors remained near nominal values. The resulting estimates were used to construct a time-varying health matrix that scales the nominal control-effectiveness matrix, producing a fault-weighted representation suitable for control allocation and supporting the objective of fault hiding. Overall, this work advances in-flight fault diagnosis by providing real-time parameter estimation for fault-tolerant control allocation, enabling redistribution of control authority to support flight operations."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["It is essential for aircraft to reliably recognize and respond when a control surface is no longer performing as intended. If an aileron, elevator, or rudder becomes stuck or loses effectiveness, the aircraft can still fly safely, provided the control system can quickly identify what changed and redistribute control effort to the remaining healthy surfaces. This thesis demonstrates how real-time modeling can be used to estimate the in-flight health of each control surface on a fixed-wing research aircraft using flight-test data. Initially, a baseline model of the aircraft was developed using test maneuvers that excite the control effectors and characterize the aircraft motion in nominal conditions. Then, multiple real-time parameter-estimation methods were evaluated using flight data containing an intentionally injected fault in the left aileron implemented through custom flight software. The methods detected a loss of the left aileron's effectiveness while indicating that the other surfaces remained healthy. These estimates were then used to construct a control-surface health matrix that could be implemented into a fault-tolerant control allocation algorithm, enabling the aircraft to shift control authority away from the degraded surface and maintain its nominal control performance."]},{"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":["Aircraft System Identification Approach for Control Surface Fault Diagnosis"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Woolsey, Craig A.","Simmons, Benjamin Mason"],"dc:contributor.committeemember":["Atkins, Ella"],"dc:contributor.department":["Aerospace and Ocean Engineering"],"dc:creator":["Corrigan, Patrick Edward"],"dc:date.accessioned":["2026-01-30T09:00:24Z"],"dc:date.available":["2026-01-30T09:00:24Z"],"dc:date.issued":["2026-01-29"],"dc:description.abstract":["Modern fault detection and diagnosis (FDD) methods are critical to maintaining flight vehicle safety. This thesis presents a model-based FDD approach for identifying control-surface loss of effectiveness on a small, fixed-wing research aircraft. The work considers several real-time system identification methods to estimate changes in control effectiveness and provide fault information to a fault-tolerant control allocation framework. A baseline aero-propulsive model for an experimental aircraft was developed from flight-test data to establish nominal control-effectiveness parameters used to compare fault diagnosis methods. Five real-time estimation methods were formulated and evaluated: exponentially weighted recursive least squares in the time- and frequency-domain, two Lyapunov-based adaptive parameter estimation methods with exponential or finite-time convergence guarantees under a persistence of excitation condition, and an augmented-state extended Kalman filter. These methods were applied to flight data containing an artificially injected stuck left-aileron fault, implemented through a custom maneuver injection capability, with multisine excitation inputs applied to the control effectors. The estimated control-effectiveness parameters associated with the faulted surface displayed an immediate response to the failure and a clear trend towards zero, while the parameters corresponding to healthy effectors remained near nominal values. The resulting estimates were used to construct a time-varying health matrix that scales the nominal control-effectiveness matrix, producing a fault-weighted representation suitable for control allocation and supporting the objective of fault hiding. Overall, this work advances in-flight fault diagnosis by providing real-time parameter estimation for fault-tolerant control allocation, enabling redistribution of control authority to support flight operations."],"dc:description.abstractgeneral":["It is essential for aircraft to reliably recognize and respond when a control surface is no longer performing as intended. If an aileron, elevator, or rudder becomes stuck or loses effectiveness, the aircraft can still fly safely, provided the control system can quickly identify what changed and redistribute control effort to the remaining healthy surfaces. This thesis demonstrates how real-time modeling can be used to estimate the in-flight health of each control surface on a fixed-wing research aircraft using flight-test data. Initially, a baseline model of the aircraft was developed using test maneuvers that excite the control effectors and characterize the aircraft motion in nominal conditions. Then, multiple real-time parameter-estimation methods were evaluated using flight data containing an intentionally injected fault in the left aileron implemented through custom flight software. The methods detected a loss of the left aileron's effectiveness while indicating that the other surfaces remained healthy. These estimates were then used to construct a control-surface health matrix that could be implemented into a fault-tolerant control allocation algorithm, enabling the aircraft to shift control authority away from the degraded surface and maintain its nominal control performance."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:45602"],"dc:identifier.uri":["https://hdl.handle.net/10919/141061"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Aircraft Modeling","Flight Test","Real-Time Parameter Estimation","Fault Detection and Diagnosis"],"dc:title":["Aircraft System Identification Approach for Control Surface Fault Diagnosis"],"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":"2026-07-22T22:19:16Z"}