Data-driven control: Recommended further reading

Steve Brunton (and Nathan Kutz)

Brunton, Steven L., and J. Nathan Kutz. Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control. Cambridge: Cambridge University Press, 2019. http://www.databookuw.com/.

Nathan Kutz (et al.)

Kutz, J. Nathan, Steven L. Brunton, Bingni W. Brunton, and Joshua L. Proctor. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems. Philadelphia: SIAM-Society for Industrial and Applied Mathematics, 2016. http://dmdbook.com/.

A very nice (and recent) overview paper is

Brunton, Steven L., Marko Budišić, Eurika Kaiser, and J. Nathan Kutz. “Modern Koopman Theory for Dynamical Systems.” ArXiv:2102.12086 [Cs, Eess, Math], February 24, 2021. http://arxiv.org/abs/2102.12086.

Another equally readable, comprehensive and recent overview paper is

Otto, Samuel E., and Clarence W. Rowley. “Koopman Operators for Estimation and Control of Dynamical Systems.” Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (2021): 59–87. https://doi.org/10.1146/annurev-control-071020-010108.

All the landmark references important in the field are surely cited in those references.

Koopman operator theory and the computational framework of (e)DMD have been used for formulating and solving control design problems by several researchers. Here I mention a close colleague of ours - Milan Korda (LAAS CNRS Toulouse, part time with us at Czech Technical University in Prague):

Korda, Milan, and Igor Mezić. “Linear Predictors for Nonlinear Dynamical Systems: Koopman Operator Meets Model Predictive Control.” Automatica 93 (July 1, 2018): 149–60. https://doi.org/10.1016/j.automatica.2018.03.046.
———. “Optimal Construction of Koopman Eigenfunctions for Prediction and Control.” IEEE Transactions on Automatic Control 65, no. 12 (December 2020): 5114–29. https://doi.org/10.1109/TAC.2020.2978039.
Korda, Milan, Mihai Putinar, and Igor Mezić. “Data-Driven Spectral Analysis of the Koopman Operator.” Applied and Computational Harmonic Analysis, August 22, 2018. https://doi.org/10.1016/j.acha.2018.08.002.

Some early (academic research) applications in the automotive domain:

Cibulka, Vít, Tomáš Haniš, Milan Korda, and Martin Hromčík. “Model Predictive Control of a Vehicle Using Koopman Operator.” IFAC-PapersOnLine, 21st IFAC World Congress, 53, no. 2 (January 1, 2020): 4228–33. https://doi.org/10.1016/j.ifacol.2020.12.2469.
Cibulka, Vít, Milan Korda, and Tomáš Haniš. “Spatio-Temporal Decomposition of Sum-of-Squares Programs for the Region of Attraction and Reachability.” IEEE Control Systems Letters 6 (2022): 812–17. https://doi.org/10.1109/LCSYS.2021.3086585.

Naposledy změněno: čtvrtek, 11. listopadu 2021, 01.05