Identification of extended Hammerstein systems for modeling sticky control valves under general types of input signals

Fang Lei 1 Jiandong Wang 1 Qinghua Zhang 2
1 College of Engineering [Beeijing]
2 SISYPHE - SIgnals and SYstems in PHysiology & Engineering
Inria Paris-Rocquencourt
Abstract : This paper is motivated by modeling the control valve stiction phenomena in feedback control loops. An extended Hammerstein system with discretized Preisach model as the input nonlinearity is proposed to capture hysteretic dynamic behaviors of cascading systems consisting of control valves followed by linear dynamic subsystems. An iterative method is p- resented to identify the extended Hammerstein systems. An informative input needs to have multiple local extreme values in order to ensure the discretized Preisach model identifiable. However, if only a single hysteresis loop of the discretized Preisach model is in active, then an oscillatory input with only two extreme values is shown to be persistently excited for identification. Hence, the proposed identification method for extended Hammerstein systems is applicable to general types of input- s as well as oscillatory ones. Two industrial examples are provided to demonstrate the effectiveness of the proposed identification method for extended Hammerstein systems.
Type de document :
Communication dans un congrès
CCC 2013 - 32nd Chinese Control Conference, Jul 2013, Xi'an, China. IEEE, pp.1698-1703, 2013
Liste complète des métadonnées
https://hal.inria.fr/hal-00854683
Contributeur : Qinghua Zhang <>
Soumis le : mardi 27 août 2013 - 18:32:12
Dernière modification le : vendredi 25 mai 2018 - 12:02:05

Identifiants

  • HAL Id : hal-00854683, version 1

Collections

INRIA

Citation

Fang Lei, Jiandong Wang, Qinghua Zhang. Identification of extended Hammerstein systems for modeling sticky control valves under general types of input signals. CCC 2013 - 32nd Chinese Control Conference, Jul 2013, Xi'an, China. IEEE, pp.1698-1703, 2013. 〈hal-00854683〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

125

Contact


archive-ouverte@inria.fr