Gaußprozessregression zur Modellierung zeitvarianter Systeme

Bergmann D, Graichen K (2019)

Publication Type: Journal article

Publication year: 2019

Journal

At-Automatisierungstechnik Oldenbourg Verlag

Book Volume: 67

Pages Range: 637-647

Journal Issue: 8

DOI: 10.1515/auto-2019-0015

Abstract

In recent times, data based methods have gained importance especially for complex and high dimensional systems due to a short development time compared to physical modeling. The disadvantage is however, that even simple knowledge such as extrapolation behaviour can in general not be considered during model generation. In this article, a modeling scheme based on Gaussian process regression is presented, which is able to incorporate such knowledge in the model. Moreover, in many systems an adaptation of the model to the individual system is necessary. To this end, an online adaptation scheme is presented, which uses the uncertainty information of the Gaussian process to detect changes in the model and incorporate them.

Authors with CRIS profile

Knut Graichen Chair of Automatic Control

Involved external institutions

Universität Ulm DE Germany (DE)

How to cite

APA:

Bergmann, D., & Graichen, K. (2019). Gaußprozessregression zur Modellierung zeitvarianter Systeme. At-Automatisierungstechnik, 67(8), 637-647. https://dx.doi.org/10.1515/auto-2019-0015

MLA:

Bergmann, Daniel, and Knut Graichen. "Gaußprozessregression zur Modellierung zeitvarianter Systeme." At-Automatisierungstechnik 67.8 (2019): 637-647.

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