In this talk, we take the unifying view of systems interacting over communication networks as distributed computing systems and propose to study them as networked control systems. Since averaging is a central operation to much science and engineering, we first study the problem of distributed averaging over unreliable networks. We show that a popular and well-behaved algorithm can instead generate a collective global complex behavior when the inter-agent communication happens over unreliable links. We characterize this behavior, common to many natural and human-made interconnected systems, as a collective hyper-jump diffusion process and a Levy flight process in a special case. To mitigate the effects of the unreliable information exchange, we propose a new distributed averaging algorithm resilient to noise and intermittent communication. The algorithm and the control perspective are the basis for the development of new distributed optimization systems that we can analyze and design as networked control systems. The approach applies to multi-agent cooperative applications and opens up several directions of research.
Nicola Elia is an Associate Professor of the Dept. of Electrical and Computer Engineering at Iowa State University. He received the Laurea degree in Electrical Engineering from Politecnico di Torino in 1987, and the Ph.D. degree in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in 1996. He worked at the Fiat Research Center from 1987 to 1990. He was Postdoctoral Associate at the Laboratory for Information and Decision Systems at MIT from 1996 to 1999. He has received the NSF CAREER Award in 2001. His research interests include networked control systems, communication systems with access to feedback, complex systems, distributed optimization and control.