Derivative-Based Koopman Operators for Real-Time Control of Robotic Systems

@article{Mamakoukas2021DerivativeBasedKO,
  title={Derivative-Based Koopman Operators for Real-Time Control of Robotic Systems},
  author={Giorgos Mamakoukas and Maria L. Casta{\~n}o and Xiaobo Tan and Todd D. Murphey},
  journal={IEEE Transactions on Robotics},
  year={2021},
  volume={37},
  pages={2173-2192}
}
This article presents a generalizable methodology for data-driven identification of nonlinear dynamics that bounds the model error in terms of the prediction horizon and the magnitude of the derivatives of the system states. Using higher order derivatives of general nonlinear dynamics that need not be known, we construct a Koopman-operator-based linear representation and utilize Taylor series accuracy analysis to derive an error bound. The resulting error formula is used to choose the order of… 

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