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Adaptive Koopman Embedding for Robust Control of Complex Nonlinear Dynamical Systems
The discovery of linear embedding is the key to the synthesis of linear control techniques for nonlinear systems. In recent years, while Koopman operator theory has become a prominent approach for learning these linear embeddings through data-driven methods, these algorithms often exhibit limitation
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