Title
Data-Driven Stabilization of Nonlinear Polynomial Systems With Noisy Data
Abstract
In a recent article, we have shown how to learn controllers for unknown linear systems using finite-length noisy data by solving linear matrix inequalities. In this article, we extend this approach to deal with unknown nonlinear polynomial systems by formulating stability certificates in the form of data-dependent sum of squares programs, whose solution directly provides a stabilizing controller and a Lyapunov function. We then derive variations of this result that lead to more advantageous controller designs. The results also reveal connections to the problem of designing a controller starting from a least-square estimate of the polynomial system.
Year
DOI
Venue
2022
10.1109/TAC.2021.3115436
IEEE Transactions on Automatic Control
Keywords
DocType
Volume
Data-driven control,nonlinear control,nonlinear systems,robust control,sum of squares
Journal
67
Issue
ISSN
Citations 
8
0018-9286
1
PageRank 
References 
Authors
0.36
15
3
Name
Order
Citations
PageRank
Meichen Guo131.06
de persis2108779.28
Pietro Tesi345232.00