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Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method
We study the quadratic prediction error method -- i. e., nonlinear least squares -- for a class of time-varying parametric predictor models satisfying a certain identifiability condition.
Structural Risk Minimization for Learning Nonlinear Dynamics
We empirically show that even though too loose to be used as absolute estimates, our SRM bounds on the true prediction error are able to track its relative behavior across different model classes of the hierarchy.
Adaptive Stochastic MPC under Unknown Noise Distribution
Then, we employ this benchmark controller to derive a novel robustly stable adaptive SMPC scheme that learns the necessary noise statistics online, while guaranteeing time-uniform satisfaction of the unknown reformulated state constraints with high probability.
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