Skip to Main content Skip to Navigation

Estimation en temps fini de systèmes non linéaires et à retards avec application aux systèmes en réseau

Abstract : This thesis investigates the topology identification problem for network of dynamical complex systems, whose subsystems are described by ordinary differential equations (ODE) and/or delay differential equations (DDE). The first part of this work focuses on the parameters identification of the network of linear systems. Thus, different classes of linear systems have been treated namely systems without delay, systems with commensurable delay and systems with unknown inputs. An impulsive observer is proposed in order to identify both the states and the unknown parameters of the considered class of dynamic system in finite time. In order to guarantee the existence of the proposed impulsive observer, sufficient conditions are deduced. An illustrative example is given in order to show the efficiency of the proposed finite-time observer.The second part of this work treats the topology identification of the network of nonlinear dynamic systems. In our considerations, 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, and then a uniform differentiator with finite-time convergence is proposed to estimate the unknown parameters
Document type :
Complete list of metadatas

Cited literature [189 references]  Display  Hide  Download
Contributor : Abes Star :  Contact
Submitted on : Tuesday, April 30, 2019 - 10:43:10 AM
Last modification on : Wednesday, October 14, 2020 - 3:40:45 AM


Version validated by the jury (STAR)


  • HAL Id : tel-02115262, version 1



Kokou Anani Agbessi Langueh. Estimation en temps fini de systèmes non linéaires et à retards avec application aux systèmes en réseau. Automatique / Robotique. Ecole Centrale de Lille, 2018. Français. ⟨NNT : 2018ECLI0012⟩. ⟨tel-02115262⟩



Record views


Files downloads