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research article

Near-Optimal Design of Safe Output-Feedback Controllers From Noisy Data

Furieri, Luca  
•
Guo, Baiwei  
•
Martin, Andrea  
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May 1, 2023
Ieee Transactions On Automatic Control

As we transition toward the deployment of data-driven controllers for black-box cyberphysical systems, complying with hard safety constraints becomes a primary concern. Two key aspects should be addressed when input-output data are corrupted by noise: how much uncertainty can one tolerate without compromising safety, and to what extent is the control performance affected? By focusing on finite-horizon constrained linear- quadratic problems, we provide an answer to these questions in terms of the model mismatch incurred during a preliminary identification phase. We propose a control design procedure based on a quasiconvex relaxation of the original robust problem and we prove that, if the uncertainty is sufficiently small, the synthesized controller is safe and near-optimal, in the sense that the suboptimality gap increases linearly with the model mismatch level. Since the proposed method is independent of the specific identification procedure, our analysis holds in combination with state-of-the-art behavioral estimators beyond standard least squares. The main theoretical results are validated by numerical experiments.

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Type
research article
DOI
10.1109/TAC.2022.3180692
Web of Science ID

WOS:000979661300006

Author(s)
Furieri, Luca  
•
Guo, Baiwei  
•
Martin, Andrea  
•
Ferrari-Trecate, Giancarlo  
Date Issued

2023-05-01

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Published in
Ieee Transactions On Automatic Control
Volume

68

Issue

5

Start page

2699

End page

2714

Subjects

Automation & Control Systems

•

Engineering, Electrical & Electronic

•

Automation & Control Systems

•

Engineering

•

safety

•

noise measurement

•

behavioral sciences

•

trajectory

•

biological system modeling

•

numerical models

•

data models

•

data-driven control

•

learning-based control

•

linear systems

•

optimal control

•

robust control

•

receding horizon control

Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
SCI-STI-GFT  
Available on Infoscience
July 3, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/198636
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