Distributed Autonomy Laboratory
Utah State University
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About Us
About Us
The Distributed Autonomy Laboratory (DAL) develops fundamental theory and algorithms toward identifiably resilient, computationally tractable, and provably robust and safe distributed partitioning, planning, and control methods for heterogeneous multi-agent systems operating autonomously in adverse conditions.
Check out our publications on Google Scholar and experiment videos on YouTube.
Research Areas
Research Areas
Recent Research Higlights
Recent Research Higlights
People
People
Director
Director
S. Burak Sarsılmaz
S. Burak Sarsılmaz
Assistant Professor in Electrical and Computer Engineering
Founding Member of Autonomy, Robotics, Control, and Optimization Group
Email: burak.sarsilmaz@usu.edu
Members
Members
K. Metehan Gül has been a PhD student since January 2024. He works on dynamic partitioning of multi-agent systems, data-driven distributed control, and their applications to networked multi-vehicle systems.
Akalu D. Teklu has been a PhD student since January 2025. He works on output regulation with input and state constraints and output formation tracking of multi-agent systems.
Benjamin A. Shunn has been an MS student since August 2025. He works on resilient trajectory planning algorithms for single and multiple vehicles.
Aws A. Alsmele has been a PhD student since January 2026. He works on resilient trajectory planning and control methods.
Recent News
Recent News
February 2026: Mete was awarded the Outstanding Graduate Researcher for the ECE Department for 2025 👏
January 2026: Akalu passed his PhD comprehensive exam 👏
January 2026: Our recent work on discrete-time cooperative output regulation via the distributed internal model approach, led by Mete, has been accepted to the 2026 American Control Conference 🎉
January 2026: Mete accepted an internship offer from the Mitsubishi Electric Research Laboratories for Summer 2026 👏
Courses
Courses
Burak has taught the following undergraduate and graduate courses, one of which he developed (Distributed Control).
Dynamic Systems and Control (Since Fall 2022, 4 instances)
Dynamic Systems and Control (Since Fall 2022, 4 instances)
Students learn mathematical modeling of systems, including transfer functions and state-space representations. They study transient and steady-state responses, feedback and stability theory, and analysis and design methods of feedback controllers for single-input single-output linear systems.
Distributed Control (Since Spring 2023, 3 instances)
Distributed Control (Since Spring 2023, 3 instances)
Students learn to analyze and synthesize distributed controllers for multi-agent systems of varying complexity and objectives using tools from graph theory, linear algebra, systems theory, and output regulation theory. The studied synchronization problems span consensus/formation of single integrators to cooperative output regulation of high-order uncertain systems.
Convex Optimization (Since Spring 2024, 3 instances)
Convex Optimization (Since Spring 2024, 3 instances)
Students learn the fundamentals of convex analysis (convex sets and functions) and optimization theory (convex optimization problems, optimality conditions, and duality theory). They receive training to recognize and formulate problems as convex optimization problems and have some experience solving such problems arising in engineering and sciences via off-the-shelf solvers.
Website last updated: February 2026
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