no code implementations • 17 May 2024 • Charis Stamouli, Lars Lindemann, George J. Pappas
We propose a shrinking-horizon MPC that guarantees recursive feasibility via a gradual relaxation of the safety constraints as new prediction regions become available online.
no code implementations • 11 Apr 2024 • Charis Stamouli, Ingvar Ziemann, George J. Pappas
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.
no code implementations • 28 Sep 2023 • Charis Stamouli, Evangelos Chatzipantazis, George J. Pappas
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.
no code implementations • 3 Apr 2022 • Charis Stamouli, Anastasios Tsiamis, Manfred Morari, George J. Pappas
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.