Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed approach involves designing a self-tuning adaptive attitude controller for unknown flexible spacecraft by identifying a high-fidelity model through numerical and experimental simulations. The models that will be compared are obtained with a lumped-mass system of unknown parameters and an interpolated model using the Theory of Functional Connections (TFC). The unknown parameters of the system are estimated with Integral Concurrent Learning (ICL) and a detailed framework for implementing this architecture onboard using real hardware is presented and validated with experimental results obtained from a real testbed. The outcome of this investigation will create opportunities to implement deployable and morphing devices on smaller spacecraft for capturing large space debris, performing propellantless deorbiting, and autonomous tethered multi-robot systems. This approach allows satellites with flexible solar arrays to maintain precise attitude without complex pre-launch modeling. The extension of the proposed ICL-based adaptive control to a post-capture scenario is presented, showing asymptotic tracking of a desired attitude trajectory for a flexible spacecraft with unknown parameters.
","abstract_html":"<p>Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed approach involves designing a self-tuning adaptive attitude controller for unknown flexible spacecraft by identifying a high-fidelity model through numerical and experimental simulations. The models that will be compared are obtained with a lumped-mass system of unknown parameters and an interpolated model using the Theory of Functional Connections (TFC). The unknown parameters of the system are estimated with Integral Concurrent Learning (ICL) and a detailed framework for implementing this architecture onboard using real hardware is presented and validated with experimental results obtained from a real testbed. The outcome of this investigation will create opportunities to implement deployable and morphing devices on smaller spacecraft for capturing large space debris, performing propellantless deorbiting, and autonomous tethered multi-robot systems. This approach allows satellites with flexible solar arrays to maintain precise attitude without complex pre-launch modeling. The extension of the proposed ICL-based adaptive control to a post-capture scenario is presented, showing asymptotic tracking of a desired attitude trajectory for a flexible spacecraft with unknown parameters.</p>","abstract_has_math":false,"creators":["Woodward, Nicolo"],"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":2025,"date_issued":"2025-10-01T07:00:00Z","date_published":"2025-10-01T07:00:00Z","updated_at":"2026-07-27T19:26:22Z","subjects":["Adaptive Control","Flexible Spacecraft","Online Learning","Integral Concurrent Learning","Spacecraft Testbed","Navigation, Guidance, Control and Dynamics","Space Vehicles"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/946","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Woodward, Nicolo"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"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":["Adaptive Control","Flexible Spacecraft","Online Learning","Integral Concurrent Learning","Spacecraft Testbed","Navigation, Guidance, Control and Dynamics","Space Vehicles"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/946"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed approach involves designing a self-tuning adaptive attitude controller for unknown flexible spacecraft by identifying a high-fidelity model through numerical and experimental simulations. The models that will be compared are obtained with a lumped-mass system of unknown parameters and an interpolated model using the Theory of Functional Connections (TFC). The unknown parameters of the system are estimated with Integral Concurrent Learning (ICL) and a detailed framework for implementing this architecture onboard using real hardware is presented and validated with experimental results obtained from a real testbed. The outcome of this investigation will create opportunities to implement deployable and morphing devices on smaller spacecraft for capturing large space debris, performing propellantless deorbiting, and autonomous tethered multi-robot systems. This approach allows satellites with flexible solar arrays to maintain precise attitude without complex pre-launch modeling. The extension of the proposed ICL-based adaptive control to a post-capture scenario is presented, showing asymptotic tracking of a desired attitude trajectory for a flexible spacecraft with unknown parameters.
"]},{"key":"dc:title","label":"Title","values":["Adaptive Control for Spacecraft with Flexible Appendages with Unknown Parameters"]}]}],"canonical_facts":{"dc:creator":["Woodward, Nicolo"],"dc:description.abstract":["Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed approach involves designing a self-tuning adaptive attitude controller for unknown flexible spacecraft by identifying a high-fidelity model through numerical and experimental simulations. The models that will be compared are obtained with a lumped-mass system of unknown parameters and an interpolated model using the Theory of Functional Connections (TFC). The unknown parameters of the system are estimated with Integral Concurrent Learning (ICL) and a detailed framework for implementing this architecture onboard using real hardware is presented and validated with experimental results obtained from a real testbed. The outcome of this investigation will create opportunities to implement deployable and morphing devices on smaller spacecraft for capturing large space debris, performing propellantless deorbiting, and autonomous tethered multi-robot systems. This approach allows satellites with flexible solar arrays to maintain precise attitude without complex pre-launch modeling. The extension of the proposed ICL-based adaptive control to a post-capture scenario is presented, showing asymptotic tracking of a desired attitude trajectory for a flexible spacecraft with unknown parameters.
"],"dc:identifier":["https://commons.erau.edu/edt/946"],"dc:subject":["Adaptive Control","Flexible Spacecraft","Online Learning","Integral Concurrent Learning","Spacecraft Testbed","Navigation, Guidance, Control and Dynamics","Space Vehicles"],"dc:title":["Adaptive Control for Spacecraft with Flexible Appendages with Unknown Parameters"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Dissertation - Open Access"],"thesis:degree_name":["Doctor of Philosophy in Aerospace Engineering"]},"updated_at":"2026-07-27T19:26:22Z"}