Nonlinear Data-Enabled Prediction and Control

Yingzhao Lian, Colin N. Jones
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:523-534, 2021.

Abstract

Behavioral theory, which characterizes linear dynamics with measured trajectories, has found successful applications in controller design and signal processing. However, the extension of behavioral theory to general nonlinear system remains an open question. In this work, we propose to apply behavioral theory to a reproducing kernel Hilbert space in order to extend its application to a class of nonlinear systems and we show its application in prediction and in predictive control.

Cite this Paper

BibTeX
@InProceedings{pmlr-v144-lian21a, title = {Nonlinear Data-Enabled Prediction and Control}, author = {Lian, Yingzhao and Jones, Colin N.}, booktitle = {Proceedings of the 3rd Conference on Learning for Dynamics and Control}, pages = {523--534}, year = {2021}, editor = {Jadbabaie, Ali and Lygeros, John and Pappas, George J. and A. Parrilo, Pablo and Recht, Benjamin and Tomlin, Claire J. and Zeilinger, Melanie N.}, volume = {144}, series = {Proceedings of Machine Learning Research}, month = {07 -- 08 June}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v144/lian21a/lian21a.pdf}, url = {https://proceedings.mlr.press/v144/lian21a.html}, abstract = {Behavioral theory, which characterizes linear dynamics with measured trajectories, has found successful applications in controller design and signal processing. However, the extension of behavioral theory to general nonlinear system remains an open question. In this work, we propose to apply behavioral theory to a reproducing kernel Hilbert space in order to extend its application to a class of nonlinear systems and we show its application in prediction and in predictive control.} }
Endnote
%0 Conference Paper %T Nonlinear Data-Enabled Prediction and Control %A Yingzhao Lian %A Colin N. Jones %B Proceedings of the 3rd Conference on Learning for Dynamics and Control %C Proceedings of Machine Learning Research %D 2021 %E Ali Jadbabaie %E John Lygeros %E George J. Pappas %E Pablo A. Parrilo %E Benjamin Recht %E Claire J. Tomlin %E Melanie N. Zeilinger %F pmlr-v144-lian21a %I PMLR %P 523--534 %U https://proceedings.mlr.press/v144/lian21a.html %V 144 %X Behavioral theory, which characterizes linear dynamics with measured trajectories, has found successful applications in controller design and signal processing. However, the extension of behavioral theory to general nonlinear system remains an open question. In this work, we propose to apply behavioral theory to a reproducing kernel Hilbert space in order to extend its application to a class of nonlinear systems and we show its application in prediction and in predictive control.
APA
Lian, Y. & Jones, C.N.. (2021). Nonlinear Data-Enabled Prediction and Control. Proceedings of the 3rd Conference on Learning for Dynamics and Control, in Proceedings of Machine Learning Research 144:523-534 Available from https://proceedings.mlr.press/v144/lian21a.html.

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