Title:
Distributionally Robust Optimization Techniques for Stochastic Optimal Control
Distributionally Robust Optimization Techniques for Stochastic Optimal Control
Author(s)
So, Chun Man Oswin
Advisor(s)
Theodorou, Evangelos A.
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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.
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Date Issued
2021-12
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Resource Type
Text
Resource Subtype
Undergraduate Thesis