Title :

Exponential stability criteria for neural network based control of nonlinear systems

Author(s) :

Jain, Ayush Kumar [Auteur]
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]
Fiter, Christophe [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Berdjag, Denis [Auteur]
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]
Polet, Philippe [Auteur]
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]

Conference title :

2020 American Control Conference (ACC)

City :

Denver

Country :

Etats-Unis d'Amérique

Start date of the conference :

2020-07-01

Publisher :

IEEE

English keyword(s) :

"Stability criteria"
"Neural networks"
"Numerical stability"
"Closed loop systems"
"Nonlinear systems"

HAL domain(s) :

Sciences de l'ingénieur [physics]/Automatique / Robotique

English abstract : [en]

This paper investigates the problem of exponential stability of neural network controlled sampled-data systems. The stability of the closed loop system is formulated using Lyapunov-Krasovskii approach. Using a time-dependent ...
Show more >This paper investigates the problem of exponential stability of neural network controlled sampled-data systems. The stability of the closed loop system is formulated using Lyapunov-Krasovskii approach. Using a time-dependent Lyapunov function, novel conditions are proposed to guarantee the exponential stability of a continuous aperiodically sampled nonlinear system. The stability conditions are derived in terms of solvable Linear Matrix Inequalities. Numerical results are provided to illustrate the effectiveness of the proposed approach.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL