Booz Allen Hamilton Colloquium: "Scalable Control of Monotone Systems"
Booz Allen Hamilton Distinguished Colloquium in Electrical and Computer Engineering
"Scalable Control of Monotone Systems"
Professor Anders Rantzer
Classical control theory does not scale well for large systems like traffic networks, power networks and chemical reaction networks. However, many of these applications can be handled efficiently using the concept of monotone system. Monotonicity means that a given state ordering is preserved by the dynamics. For example, a system is called monotone if all step responses are monotone. Such systems are common in many branches of science and engineering.
In this presentation, we will highlight several fundamental advantages of monotone control systems: Verification and performance optimization can be done in with a complexity that scales linearly with the number of states and interconnections. Distributed controllers can be designed by convex optimization. Lyapunov functions and storage functions for nonlinear monotone systems can be built from scalar functions of the states, with dramatic simplifications as a result.
Anders Rantzer received a PhD in 1991 from KTH, Stockholm, Sweden. After postdoctoral positions at KTH and at IMA, University of Minnesota, he joined Lund University in 1993 and was appointed professor of Automatic Control in 1999. The academic year of 2004/05 he was visiting associate faculty member at Caltech. Since 2008 he coordinates the Linnaeus center LCCC at Lund University. For the period 2013-15 he is also chairman of the Swedish Scientific Council for Natural and Engineering Sciences.
Rantzer has been associate editor of IEEE Transactions on Automatic Control and several other journals. He is a winner of the SIAM Student Paper Competition, the IFAC Congress Young Author Price and the IET Premium Award for the best article in IEE Proceedings - Control Theory & Applications during 2006. He is a Fellow of IEEE and a member of the Royal Swedish Academy of Engineering Sciences.
His research interests are in modeling, analysis and synthesis of control systems, with particular attention to uncertainty, optimization and distributed control.