Creator:

Mrugalski, Marcin

Contributor:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Title:

An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection

Group publication title:

AMCS, Volume 23 (2013)

Subject and Keywords:

robust fault detection ; non-linear system identification ; dynamic GMDH neural network ; unscented Kalman filter

Abstract:

This paper presents an identification method of dynamic systems based on a group method of data handling approach. In particular, a new structure of the dynamic multi-input multi-output neuron in a state-space representation is proposed. Moreover, a new training algorithm of the neural network based on the unscented Kalman filter is presented. The final part of the work contains an illustrative example regarding the application of the proposed approach to robust fault detection of a tunnel furnace.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2013

Resource Type:

artykuł

DOI:

10.2478/amcs-2013-0013

Pages:

157-169

Source:

AMCS, volume 23, number 1 (2013) ; click here to follow the link

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego