Topology identification of network systems
Document type :
Communication dans un congrès avec actes
Title :
Topology identification of network systems
Author(s) :
Langueh, Kokou [Auteur]
Non-Asymptotic estimation for online systems [NON-A]
Zheng, Gang [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Deformable Robots Simulation Team [DEFROST ]
Floquet, Thierry [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Non-Asymptotic estimation for online systems [NON-A]
Zheng, Gang [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Deformable Robots Simulation Team [DEFROST ]
Floquet, Thierry [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Conference title :
CDC 2017 - 56th IEEE Conference on Decision and Control
City :
Melbourne
Country :
Australie
Start date of the conference :
2017-12-12
HAL domain(s) :
Informatique [cs]/Automatique
English abstract : [en]
— This paper investigates the topology identification problem for network systems, whose subsystems are described by ODEs. In our study, the topology connections are represented as constant parameters, therefore the topology ...
Show more >— This paper investigates the topology identification problem for network systems, whose subsystems are described by ODEs. In our study, the topology connections are represented as constant parameters, therefore the topology identification is equivalent to identify the unknown parameters. A sufficient condition on parameter identifiability is firstly deduced in this paper, and then a uniform differentiator with fixed-time convergence is proposed to estimate the unknown parameters.Show less >
Show more >— This paper investigates the topology identification problem for network systems, whose subsystems are described by ODEs. In our study, the topology connections are represented as constant parameters, therefore the topology identification is equivalent to identify the unknown parameters. A sufficient condition on parameter identifiability is firstly deduced in this paper, and then a uniform differentiator with fixed-time convergence is proposed to estimate the unknown parameters.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :