A novel constraint‐tightening approach for robust data‐driven predictive control-Reference-Cited by-同舟云学术

A novel constraint‐tightening approach for robust data‐driven predictive control

Published:2022-12-07 Issue: Volume: Page:
ISSN:1049-8923
Container-title:International Journal of Robust and Nonlinear Control
language:en
Short-container-title:Intl J Robust & Nonlinear

Author:

Klöppelt Christian¹^ORCID,Berberich Julian²^ORCID,Allgöwer Frank²^ORCID,Müller Matthias A.¹^ORCID

Affiliation:

1. Institute of Automatic Control Leibniz University Hannover Hannover Germany

2. Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany

Funder

Deutsche Forschungsgemeinschaft

Stuttgart Center for Simulation Science

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rnc.6532

Reference34 articles.

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3. CoulsonJ LygerosJ DörflerF.Data‐enabled predictive control: in the shallows of the DeePC. Proceedings of the 2019 18th European Control Conference (ECC);2019:307‐312; IEEE.

4. Data‐driven model predictive control with stability and robustness guarantees;Berberich J;IEEE Trans Automat Contr,2020

5. Distributionally robust chance constrained data‐enabled predictive control;Coulson J;IEEE Trans Automat Contr,2021

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