Title:
Distributionally Robust Optimization Techniques for Stochastic Optimal Control

Thumbnail Image
Author(s)
So, Chun Man Oswin
Authors
Advisor(s)
Theodorou, Evangelos A.
Advisor(s)
Editor(s)
Associated Organization(s)
Organizational Unit
Organizational Unit
School of Computer Science
School established in 2007
Supplementary to
Abstract
Distributionally robust optimal control is a relatively new field of robust control that tries to address the issue of safety by hedging against the worst-cast distributions. However, because probability distributions are infinite-dimensional, this problem is in general computationally intractable. This thesis provides an overview of applications of distributionally robust optimization for stochastic optimal control. In particular, we look at existing and potentially new computationally tractable methods for performing distributionally robust optimal control using the Wasserstein metric.
Sponsor
Date Issued
2021-12
Extent
Resource Type
Text
Resource Subtype
Undergraduate Thesis
Rights Statement
Rights URI