Deep bilinear Koopman realization for dynamics modeling and predictive control
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13042-023-02095-y.pdf
Reference52 articles.
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2. Zinage V, Bakolas E (2023) Neural Koopman Lyapunov control. Neurocomputing 527:174–183. https://doi.org/10.1016/j.neucom.2023.01.029
3. Korda M, Mezić I (2016) Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control. Automatica 93:149–160. https://doi.org/10.1016/j.automatica.2018.03.046
4. Proctory JL, Brunton SL, Kutz JN (2016) Generalizing Koopman theory to allow for inputs and control. SIAM J Appl Dyn Syst 17:909–930. https://doi.org/10.1137/16M1062296
5. Korda M, Mezić I (2020) Optimal construction of Koopman eigenfunctions for prediction and control. IEEE Trans Autom Control 65(12):5114–5129. https://doi.org/10.1109/TAC.2020.2978039
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