User: Guest  Login

There is a newer version of the object available.

Document type:
Konferenzbeitrag
Contribution type:
Textbeitrag / Aufsatz
Author(s):
Capone, A.; Hirche, S.
Title:
Interval Observers for a Class of Nonlinear Systems Using Gaussian Process Models
Abstract:
An interval observer design approach for partially unknown nonlinear systems is developed, where the unknown system component is modeled using Gaussian processes and noisy system measurements. The proposed method is applicable for bounded nonlinear systems where the system uncertainty is described by a Lipschitz continuous function. The interval observer generates a correct estimation error with high probability, and the error bound is decreased by employing new training data points
Keywords:
Gaussian process, data-driven, machine learning, interval observer, nonlinear system
Dewey Decimal Classification:
000 Informatik, Wissen, Systeme
Book / Congress title:
2019 18th European Control Conference
Date of congress:
25-28 June 2019
Publisher:
IEEE
Year:
2019
 BibTeX
versions