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Communication Dans Un Congrès Année : 2023

High-gain like observer design for nonlinear systems applied to vehicle motion estimation

Cédric Delattre
  • Fonction : Auteur
  • PersonId : 902060
  • IdRef : 220479631
Zehor Belkhatir
  • Fonction : Auteur
  • PersonId : 1158996
Ali Zemouche
Rajesh Rajamani
  • Fonction : Auteur
  • PersonId : 974809

Résumé

This work investigates the problem of state estimation for nonlinear triangular systems having additional output measurements. The main objective of this paper is to propose observer design strategies that account for the available additional information, which is difficult to consider using the standard high-gain observer methodology. To deal with this challenge, we propose two novel observer design methods to handle the additional output measurements. The first method can be thought of as an extension of the standard high-gain observer by introducing a weighting matrix as a tuning parameter. The second method, however, which uses both the high-gain methodology and the LPV/LMI technique, is proposed to overcome some limitations associated with the first design method. To proposed two approaches were applied to a nonlinear longitudinal dynamic model that uses extra measurement information, in addition to the measured longitudinal position of the vehicle.

Domaines

Automatique
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Dates et versions

hal-04016125 , version 1 (06-03-2023)

Identifiants

  • HAL Id : hal-04016125 , version 1

Citer

Hichem Bessafa, Cédric Delattre, Zehor Belkhatir, Ali Zemouche, Rajesh Rajamani. High-gain like observer design for nonlinear systems applied to vehicle motion estimation. 22nd IFAC World Congress, IFAC 2023, Jul 2023, Yokohama, Japan. ⟨hal-04016125⟩
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