Skip to Main content Skip to Navigation
Journal articles

Generalized LMI observer design for discrete-time nonlinear descriptor models

Abstract : The present paper provides a systematic way to generalize Takagi-Sugeno observer design for discrete-time nonlinear descriptor models. The approach is based on Finsler's lemma, which decouples the observer gains from the Lyapunov function. The results are expressed as strict LMI constraints. To obtain more degrees of freedom without altering the number of LMI constraints and thus relax the conditions, delayed Lyapunov functions and delayed observer gains are considered. Even more relaxed results are developed by extending the approach to α-sample variation. The effectiveness of the proposed methods is illustrated via examples.
Document type :
Journal articles
Complete list of metadata

https://hal-uphf.archives-ouvertes.fr/hal-03426862
Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Friday, November 12, 2021 - 4:01:12 PM
Last modification on : Saturday, November 13, 2021 - 3:53:30 AM

Identifiers

Collections

Citation

Víctor Estrada Manzo, Zsofia Lendek, Thierry-Marie Guerra. Generalized LMI observer design for discrete-time nonlinear descriptor models. Neurocomputing, Elsevier, 2016, 182, pp.210-220. ⟨10.1016/j.neucom.2015.12.033⟩. ⟨hal-03426862⟩

Share

Metrics

Record views

12