Title: Distributionally robust control of constrained stochastic systems
Speaker: Bart Van Parys
Affiliation: Automatic Control Laboratory at Swiss Federal Institute of Technology
Location: Room 217-218 Huxley Building
Time: 2:00pm

Abstract. We investigate the control of constrained stochastic linear systems when faced with limited information regarding the disturbance process, that is, when only the first and second-order moments of the disturbance distribution are known.
We employ two types of soft constraints to prevent the state from falling outside a prescribed target domain: distributionally robust chance constraints require the state to remain within the target domain with a given high probability, while distributionally robust conditional value-at-risk constraints impose an upper bound on the state’s expected distance to the target domain conditional on that distance being positive.
The attribute 'distributionally robust' reflects the requirement that the constraints must hold for all disturbance distributions sharing the known moments. We argue that the design of controllers for systems accommodating these types of constraints is both computationally tractable and practically meaningful for both finite and infinite horizon problems.
The proposed methods are illustrated in the context of a wind turbine blade control design case study where flexibility issues play an important role and for which the distributionally robust constraints make sensible design objectives.

About the speaker. Bart holds a BA degree in electrical engineering, and a MA degree in applied/engineering mathematics, both from the University of Leuven. Since September 2011 he has been a PhD student in the Swiss Federal Institute of Technology (ETH Zürich) under the supervision of Prof. Manfred Morari and Dr. Paul Goulart.