Skip to main navigation Skip to main content
The University of Southampton
CORMSIS Centre for Operational Research, Management Sciences and Information Systems

CORMSIS seminar: Distributionally Robust Optimisation and Control with Structured Uncertainty Event

Time:
16:00 - 17:00
Date:
28 January 2016
Venue:
Building 02 Room 3041, Southampton Business School

For more information regarding this event, please email Yuan Huang at yuan.huang@soton.ac.uk .

Event details

Abstract: This talk will address the problem of quantifying the expected value of some function of a random variable with unknown distribution. Typical problems of this type include determining the expected profit of a stock portfolio with uncertain returns and quantifying the symbol error rate in a noisy communication channel. In particular, the talk will address cases in which only limited or ambiguous moment information is available, but some additional structural properties – e.g. symmetry, unimodality or monotonicity – are known to hold. In such cases, one can compute a sharp upper bound on the worst-case expectation, taken over all distributions satisfying the partial moment and other structural information available. The results can also be applied to control of linear systems with chance constraints, for which robust conditional Value-at-Risk (CVaR) conditions can be used to control both the probability and the degree of constraint violations.

Speaker information

Dr Paul Goulart ,University of Oxford,Bio: Paul Goulart is an Associate Professor in Control Engineering in the University of Oxford. From 2011 to 2014 he was a senior researcher in the Automatic Control Laboratory at ETH Zurich, and from 2007 to 2011 a lecturer in control systems in the Department of Aeronautics at Imperial College London. He received BSc and MSc degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology (MIT). He was selected as a Gates Scholar at the University of Cambridge, where he received a PhD in Control Engineering in 2007. His research interests include model predictive control, robust optimization and control of fluid flows.

Privacy Settings