8 citations · 19 across the 10 of their papers we have counts for
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math.OC2024★ 3 cited
Kernel-based Koopman approximants for control: Flexible sampling, error analysis, and stability
Lea Bold, Friedrich M. Philipp, Manuel Schaller +1
Data-driven techniques for analysis, modeling, and control of complex dynamical systems are on the uptake. Koopman theory provides the theoretical foundation for the popular kernel…
eess.SY2024★ 8 cited
Data-Driven Predictive Control of Nonholonomic Robots Based on a Bilinear Koopman Realization: Data Does Not Replace Geometry
Mario Rosenfelder, Lea Bold, Hannes Eschmann +3
Advances in machine learning and the growing trend towards effortless data generation in real-world systems has led to an increasing interest for data-inferred models and data-base…