Stochastic observers on Lie groups: a tutorial - Mines Paris Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Stochastic observers on Lie groups: a tutorial

Axel Barrau
  • Fonction : Auteur
  • PersonId : 941948
Silvère Bonnabel
  • Fonction : Auteur
  • PersonId : 866182

Résumé

In this tutorial paper, we discuss the design of geometric observers on Lie groups in the presence of noise. First we review Lie groups, and the mathematical definition of noises on Lie groups, both in discrete and continuous time. In particular, we discuss the It\^o-Stratonovich dilemma. Then, we review the recently introduced notion of group affine systems on Lie groups. For those systems, we discuss how using the machinery of Harris chains, (almost) globally convergent deterministic observers might be shown to possess stochastic properties in the presence of noise. We also discuss the design of (invariant) extended Kalman filters (IEKF), and we recall the main result, i.e., the Riccati equation computed by the filter to tune its gains has the remarkable property that the Jacobians (A,C) with respect to the system's dynamics and output map are independent of the followed trajectory, whereas the noise covariance matrices that appear in the Riccati equation may depend on the followed trajectory. Owing to this partial independence, some local deterministic convergence properties of the IEKF for group-affine systems on Lie groups may be proved under standard observability conditions.
Fichier principal
Vignette du fichier
CDC_tutorial.pdf (282.18 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01826025 , version 1 (28-06-2018)
hal-01826025 , version 2 (07-10-2018)

Identifiants

  • HAL Id : hal-01826025 , version 2

Citer

Axel Barrau, Silvère Bonnabel. Stochastic observers on Lie groups: a tutorial. IEEE Conference on Decision and Control, IEEE, Dec 2018, Miami, United States. ⟨hal-01826025v2⟩
421 Consultations
1675 Téléchargements

Partager

Gmail Facebook X LinkedIn More