Control and Optimization in Complex Networks of Dynamical Systems

Tyler H. Summers (ETH Zurich)

SYSTEMS AND CONTROL SERIES

DATE: 2013-10-30
TIME: 16:00:00 - 17:00:00
LOCATION: RSISE Seminar Room, ground floor, building 115, cnr. North and Daley Roads, ANU
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ABSTRACT:
The first part of the talk describes a basic sensor and actuator placement for a large dynamical network: choose a subset from a finite set of possible placements to optimize some real-valued controllability and observability metrics of the network. I will show that an important class of metrics based on the controllability and observability Gramians has a strong structural property that allows efficient global optimization: the mapping from possible placements to the trace of the associated Gramian is a modular set function.

The second part describes a distributed optimization method for solving distributed model predictive control and consensus problems. The goal is to design a distributed controller for a network of dynamical systems to optimize a coupled objective function while respecting state and input constraints. The distributed optimization method is an augmented Lagrangian method called the Alternating Direction Method of Multipliers (ADMM), which was introduced in the 1970s but has seen a recent resurgence in the context of dramatic increases in computing power and the development of widely available distributed computing platforms.

BIO:
Tyler Summers is an ETH Postdoctoral Fellow at the Automatic Control Laboratory at ETH Zurich, Switzerland. He received a B.S. degree in Mechanical Engineering from Texas Christian University in 2004 and an M.S. and PhD degree in Aerospace Engineering with emphasis on feedback control theory at the University of Texas at Austin in 2007 and 2010, respectively. He was a Fulbright Postgraduate Scholar at the Australian National University in Canberra, Australia in 2007-2008 and was designed as the Australian-American Alumni Scholar as the top-ranked applicant to Australia. He received an ETH Postdoctoral Fellowship and has been with the Automatic Control Laboratory at ETH Zurich since 2011. His research focuses on control and optimization in complex networks with applications to autonomous vehicle formations, power networks, social networks, and biological networks.