33 citations · 42 across the 3 of their papers we have counts for
3 papers
eess.SY2021★ 33 cited
Data-driven distributionally robust MPC for constrained stochastic systems
Peter Coppens, Panagiotis Patrinos
In this paper we introduce a novel approach to distributionally robust optimal control that supports online learning of the ambiguity set, while guaranteeing recursive feasibility.…
eess.SY2020★ 7 cited
Sample Complexity of Data-Driven Stochastic LQR with Multiplicative Uncertainty
Peter Coppens, Panagiotis Patrinos
This paper studies the sample complexity of the stochastic Linear Quadratic Regulator when applied to systems with multiplicative noise. We assume that the covariance of the noise…
eess.SY2019★ 2 cited
Data-driven distributionally robust LQR with multiplicative noise
Peter Coppens, Mathijs Schuurmans, Panagiotis Patrinos
We present a data-driven method for solving the linear quadratic regulator problem for systems with multiplicative disturbances, the distribution of which is only known through sam…