Abstract: The study of large scale and complex interconnected systems is of great importance in today's networked world with applications ranging from distributed power generation to deep space exploration. A great challenge for these systems is to understand the interplay between the dynamic properties of the individual systems comprising the networks, the underlying information exchange network, and the interaction protocols governing the collective behavior. In this talk we will explore necessary and sufficient conditions for a network of passive dynamical systems to reach an output agreement, i.e., the trajectories of each system will synchronize. This leads to a refinement of classical passivity theory that we term maximal equilibrium passivity. We then show that the steady-state behavior of these systems are in fact solutions to a family of classic network optimization problems, and as a result we draw connections between notions of duality in static optimization to cooperative control. This network optimization perspective also leads to synthesis methods for controllers to guarantee the desired behavior of the network and provides new insights to classical problems such as feedback passivation.
Bio: Daniel Zelazo is an associate professor of aerospace engineering and director of the Philadelphia Flight Control Laboratory at the Technion-Israel Institute of Technology, Haifa. He received the B.Sc. and M.Eng. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, in 1999 and 2001, respectively. In 2009, he completed his Ph.D. degree at the University of Washington, Seattle, in aeronautics and astronautics. From 2010 to 2012, he was a postdoctoral research associate and lecturer at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany. He is currently an associate editor of IEEE Control Systems Letters and subject editor for the International Journal of Robust and Nonlinear Control. His research interests include topics related to multi-agent systems, graph theory, and control systems.
