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Distributed Control, Estimation and Optimization in Multi-agent Systems

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Abstract:While autonomous systems that perform solo missions can yield significant benefits, greater efficiency and operational capability will be realized from teams of autonomous systems operating in a coordinated fashion. Potential applications for networked multiple autonomous systems include environmental monitoring, search and rescue, space-based interferometers, hazardous material handling, and combat, surveillance, and reconnaissance systems. Networked multi-agent systems place high demands on features such as low cost, high adaptivity and scalability, increased flexibility, great robustness, and easy maintenance. To meet these demands, the current trend is to design distributed algorithms that rely on only local information and local interaction to achieve global group behavior.

The purpose of this talk is to overview our recent research in distributed control, estimation and optimization in networked multi-agent systems. For distributed control, results on distributed synchronization for agents with various dynamics, distributed single-leader collective tracking with reduced interaction and partial measurements, and distributed multi-leader containment control with local interaction will be introduced. For distributed estimation, results on fully distributed information fusion with multiple networked sensors will be introduced, under very mild assumptions on local observability, communication graphs, and models. For distributed optimization, results on distributed convex optimization will be introduced, under realistic challenges such as non-identical constraints, fully distributed design, and time-varying cost functions. Application examples in multi-vehicle cooperative control will also be introduced.

This talk is part of the CUED Control Group Seminars series.

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