Scalable Control and Verification for Networks
Prof. Murat Arak, U.C. Berkeley, Electrical Engineering and Computer Sciences (EECS)
03.07.2017, 10:30, room 4981
Existing computational methods for control and verification are applicable only to problems of modest size and do not scale to today’s network control systems. To overcome this limitation, in this talk we advocate: (1) deriving network level guarantees from the subsystems with a bottom-up compositional procedure, and (2) exploiting key structural network properties. We identify such properties in applications such as multi-agent robotic systems, vehicle traffic networks, and synthetic biology, and generalize them to broader classes of systems. In the first part of the talk we present a compositional methodology where we make use of input/output properties of the subsystems to derive network level stability, performance, and safety guarantees. In the second part we address more complex control specifications expressed in temporal logic and leverage formal methods for control synthesis. In particular we overcome obstacles to scalability in this procedure by exploiting monotone dynamics and demonstrate the results on vehicle traffic networks. In the third part we apply our compositional network analysis techniques to spatial pattern formation in biology, a phenomenon that is central to multicellular development where gene expression patterns enable distinct cell types to emerge.
Murat Arcak is a professor at U.C. Berkeley in the Electrical Engineering and Computer Sciences (EECS) Department. He received the B.S. degree in Electrical Engineering from the Bogazici University, Istanbul (1996) and the M.S. and Ph.D. degrees from the University of California, Santa Barbara (1997 and 2000). His research is in dynamical systems and control theory with applications to synthetic biology, multi-agent systems, and transportation networks. Prior to joining Berkeley in 2008, he was a faculty member at the Rensselaer Polytechnic Institute and held visiting positions at the University of Melbourne and the Massachusetts Institute of Technology. He received a CAREER Award from the National Science Foundation in 2003, the Donald P. Eckman Award from the American Automatic Control Council in 2006, the Control and Systems Theory Prize from the Society for Industrial and Applied Mathematics (SIAM) in 2007, the Antonio Ruberti Young Researcher Prize from the IEEE Control Systems Society in 2014, and the Outstanding Teaching Award from the EECS Department in 2014. He is a member of SIAM and a fellow of IEEE.