Interval Prediction for Continuous-Time ...
Document type :
Communication dans un congrès avec actes
Title :
Interval Prediction for Continuous-Time Systems with Parametric Uncertainties
Author(s) :
Leurent, Edouard [Auteur]
RENAULT
Finite-time control and estimation for distributed systems [VALSE]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Raissi, Tarek [Auteur]
Conservatoire National des Arts et Métiers [CNAM] [CNAM]
Perruquetti, Wilfrid [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
RENAULT
Finite-time control and estimation for distributed systems [VALSE]
Efimov, Denis [Auteur]

Finite-time control and estimation for distributed systems [VALSE]
Raissi, Tarek [Auteur]
Conservatoire National des Arts et Métiers [CNAM] [CNAM]
Perruquetti, Wilfrid [Auteur]

Finite-time control and estimation for distributed systems [VALSE]
Conference title :
58th IEEE Conference on Decision and Control
City :
Nice
Country :
France
Start date of the conference :
2019-12-11
HAL domain(s) :
Informatique [cs]/Automatique
English abstract : [en]
The problem of behaviour prediction for linear parameter-varying systems is considered in the interval framework. It is assumed that the system is subject to uncertain inputs and the vector of scheduling parameters is ...
Show more >The problem of behaviour prediction for linear parameter-varying systems is considered in the interval framework. It is assumed that the system is subject to uncertain inputs and the vector of scheduling parameters is unmeasurable, but all uncertainties take values in a given admissible set. Then an interval predictor is designed and its stability is guaranteed applying Lyapunov function with a novel structure. The conditions of stability are formulated in the form of linear matrix inequalities. Efficiency of the theoretical results is demonstrated in the application to safe motion planning for autonomous vehicles.Show less >
Show more >The problem of behaviour prediction for linear parameter-varying systems is considered in the interval framework. It is assumed that the system is subject to uncertain inputs and the vector of scheduling parameters is unmeasurable, but all uncertainties take values in a given admissible set. Then an interval predictor is designed and its stability is guaranteed applying Lyapunov function with a novel structure. The conditions of stability are formulated in the form of linear matrix inequalities. Efficiency of the theoretical results is demonstrated in the application to safe motion planning for autonomous vehicles.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Comment :
Webpage: https://eleurent.github.io/interval-prediction/
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