An MCMC Method for Uncertainty Set Generation via Operator-Theoretic Metrics

@article{Srinivasan2020AnMM,
  title={An MCMC Method for Uncertainty Set Generation via Operator-Theoretic Metrics},
  author={Anand Srinivasan and Naoya Takeishi},
  journal={2020 59th IEEE Conference on Decision and Control (CDC)},
  year={2020},
  pages={2714-2719}
}
Model uncertainty sets are required in many robust optimization problems, such as robust control and prediction with uncertainty, but there is no definite methodology to generate uncertainty sets for nonlinear dynamical systems. In this paper, we propose a method for model uncertainty set generation via Markov chain Monte Carlo. The proposed method samples from distributions over dynamical systems via metrics over transfer operators and is applicable to general nonlinear systems. We adapt… Expand

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