Author

Kazuhiro Sato

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Preprint Sep 2026

Contraction-Based Model Predictive Control using Bilinear Koopman Realizations with Proportional Error Bounds

Data-driven model predictive control based on Koopman operator theory is a promising approach for constrained control of nonlinear systems with unknown dynamics. This paper proposes a robust model predictive control framework for such systems using bilinear Koopman realizations with state- and input-dependent proportio...

Yuki Higuchi, Kazuhiro Sato · 0 citations

Preprint Jul 2026

Bilinear Koopman-Based Robust Model Predictive Control for Unknown Nonlinear Systems via Contraction Metrics

A RMPC framework for unknown nonlinear systems with general nonlinear constraints based on data-driven bilinear Koopman realizations is proposed and robust satisfaction of the original nonlinear constraints is proved by the true closed-loop trajectory, recursive feasibility, and convergence to a neighborhood of the tar...

Yuki Higuchi, Kazuhiro Sato · 1 citation