A Wasserstein distributionally robust data-driven predictive control framework for unknown stochastic LTI systems that yields a tractable reformulation with high-probability bounds on true expected cost and output constraints.
Bridging direct and indirect data-driven control formulations via regularizations and relaxations.IEEE Transactions on Automatic Control, 68(2):883–897
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Distributionally Robust Data-Driven Predictive Control for Stochastic LTI Systems
A Wasserstein distributionally robust data-driven predictive control framework for unknown stochastic LTI systems that yields a tractable reformulation with high-probability bounds on true expected cost and output constraints.