Date of Award
10-28-2024
Publication Type
Dissertation
Degree Name
Ph.D.
Department
Mechanical, Automotive, and Materials Engineering
Keywords
Clustered Satellite Network;Fault Diagnosis;Interconnected Autonomous Vehicles;Robust Control;State Estimation
Supervisor
Afshin Rahimi
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
The main objective of this study was to advance the field of fault diagnosis in multi-agent systems (MASs), with a particular focus on small satellite constellations operating in space. The motivation behind this research stems from the increasing deployment of MAS in complex environments, necessitating reliable strategies to ensure mission success. The study begins by discussing the importance of coordinated control in MAS and the inherent reliability issues due to challenging operational conditions. It emphasizes the significance of enhancing system safety through fault diagnosis and prognosis (FDP) and fault-tolerant control (FTC) approaches. The research underscores the advantages of using constellations of small satellites over single large satellites, including cost efficiency, versatility in mission capabilities, and increased fault tolerance through redundancy. A comprehensive survey of state-of-the-art FDP techniques is presented, highlighting recent advancements and identifying gaps in the current literature. The research introduces a novel distributed H∞-based robust fault estimation and cluster consensus control approach tailored for small satellite clusters by employing unknown input observers (UIOs) to mitigate external disturbances effect while achieving consensus in the presence of nonlinearities and faults. The dissertation further explores robust fault diagnosis strategies including fault detection, isolation, and identification for heterogeneous satellite clusters, utilizing augmented vectors and directed communication graphs to diagnose states and faults. An innovative dissipativity-based method is proposed to handle scenarios where traditional matching conditions are not met, enhancing fault estimation precision and robustness. Additionally, the research addresses fault diagnosis in formation flying of agents with nonlinearities, introducing an adjustable parameter-based UIO for precise fault detection and approximation. A hybrid fault-tolerant cooperative control (HFTCC) method is then developed, combining passive and active FTC strategies to handle concurrent actuator faults in nonlinear MASs. This hybrid approach significantly improves the convergence time and reduces estimation errors in clustered MASs. The dissertation concludes by summarizing the key contributions and implications of the research, providing a foundation for future work in fault diagnosis and control in satellite constellations. The findings offer innovative solutions for enhancing the reliability and operational efficiency of MASs in space, ensuring sustained mission success.
Recommended Citation
Barzegar, Ailin, "Development of Model-based Fault Diagnosis for in-Orbit Small Satellites in Constellation" (2024). Electronic Theses and Dissertations. 9384.
https://scholar.uwindsor.ca/etd/9384