In linear systems with parametric uncertainty and Gaussian noise, MPC policy dependence on posterior covariance peaks at high uncertainty and vanishes as it contracts, with the dual controller outperforming certainty-equivalent MPC on both regulation performance and model accuracy.
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The Separation Principle and the Dual-Certainty Equivalence Gap in Model Predictive Control
In linear systems with parametric uncertainty and Gaussian noise, MPC policy dependence on posterior covariance peaks at high uncertainty and vanishes as it contracts, with the dual controller outperforming certainty-equivalent MPC on both regulation performance and model accuracy.