Advertisement
Published in:
2018 | OriginalPaper | Chapter
Fast and Robust Online Dynamic System Identification
Author : Andrzej Latocha
Published in: Advanced Solutions in Diagnostics and Fault Tolerant Control
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
A new method is proposed for black-box linear model identification of a dynamic system embedded at a nearly Gaussian noise. The Gaussian process can highlight areas of the output spaces where the prediction quality is poor, due to the lack of data or its complexity, by indicating the higher variance of the predicted mean; the input spaces in which we can reconstruct data represent the expected values. This paper proposed a new approach for the online system identification for non-zero initial conditions in the moving window.