A Grassmannian-metric-ball model of data uncertainty yields a closed-form robust least-squares solver that strengthens robustness and scaling in finite-horizon data-driven predictive control.
Jean-Pierre Delmas
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Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
A Grassmannian-metric-ball model of data uncertainty yields a closed-form robust least-squares solver that strengthens robustness and scaling in finite-horizon data-driven predictive control.