Graduation Semester and Year
Fall 2026
Language
English
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science and Engineering
First Advisor
Dr. Md Salik Parwez
Second Advisor
Dr. Debashri Roy
Third Advisor
Dr. Nadra Guizani
Abstract
Low-altitude unmanned aerial vehicle (UAV) swarms are increasingly used in applications such as aerial sensing, disaster response, and communication support, where reliable operation under dynamic and uncertain conditions is essential. In these environments, performance degradation arises from multiple sources, including external disturbances, sensing uncertainty, and communication impairments. Although these effects originate from different layers of the system, such as dynamics, observation, and networking, they often manifest as similar tracking or coordination errors. Conventional control approaches, which rely primarily on error-driven feedback, do not explicitly account for the underlying cause of these deviations, limiting their effectiveness in multi-agent settings. This thesis presents a cross-layer supervisory control framework that augments a classical proportional–integral–derivative (PID) controller with a lightweight supervisory layer. The supervisory mechanism monitors the behavior of the system in multiple layers, identifies likely fault conditions, and applies bounded adaptations to the reference motion, the geometry of the formation and the coordination parameters, allowing differentiated responses while preserving nominal stability. The framework is evaluated in a multi-UAV simulation environment with controlled fault injection and multi-seed experimentation. Results show improved robustness under disturbance and communication faults, with reduced tracking error and faster recovery, while maintaining comparable nominal performance. Improvements under sensing faults are more limited, highlighting the role of state estimation. Overall, this work demonstrates that cross-layer supervisory adaptation can enhance swarm resilience without increasing control complexity, providing a practical foundation for robust UAV swarm operation in low-altitude environments.
Keywords
UAV swarm, PID control, supervisory control, fault-aware control, cross-layer control, multi-UAV systems, swarm resilience, communication-aware coordination, low-altitude wireless networks, fault-tolerant UAV systems
Disciplines
Robotics
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Rathore, Nitin Singh, "Cross-Layer Supervisory Control for Low-Altitude UAV Swarm Networks" (2026). Computer Science and Engineering Theses. 7.
https://mavmatrix.uta.edu/cse_theses2/7