Factorially Switching Dynamic Mode Decomposition for Koopman Analysis of Time-Variant Systems

@article{Takeishi2018FactoriallySD,
  title={Factorially Switching Dynamic Mode Decomposition for Koopman Analysis of Time-Variant Systems},
  author={Naoya Takeishi and Takehisa Yairi and Yoshinobu Kawahara},
  journal={2018 IEEE Conference on Decision and Control (CDC)},
  year={2018},
  pages={6402-6408}
}
The modal decomposition based on the spectra of the Koopman operator has gained much attention in various areas such as data science and optimal control, and dynamic mode decomposition (DMD) has been known as a data-driven method for this purpose. However, there is a fundamental limitation in DMD and most of its variants; these methods are based on the premise that the target system is time-invariant at least within the data at hand. In this work, we aim to compute DMD on time-varying dynamical… CONTINUE READING
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