Redesign of discrete-time nonlinear observers with state estimate constraints guaranteed in prescribed convex set

Daniele Astolfi (1, 2) , Pauline Bernard (3) , Romain Postoyan (4) , Lorenzo Marconi (5)

1 CNRS - Centre National de la Recherche Scientifique
2 LAGEPP - Laboratoire d'automatique, de génie des procédés et de génie pharmaceutique
3 CAS - Centre Automatique et Systèmes
4 CRAN - Centre de Recherche en Automatique de Nancy
5 UNIBO - Alma Mater Studiorum Università di Bologna = University of Bologna

We propose a technique to modify a given discrete-time (nonlinear) observer so that the state estimate remains in a given convex set, without altering the observer performances in terms of convergence and robustness to external disturbances. The proposed approach can be used to remove the peaking phenomenon or to attenuate the effect of impulsive outliers in the measures. it assumes that it is possible to execute a certain number of computations between any two sampling times in order to refine the current estimate and bring it back into the prescribed set. The proposed technique can be applied to any class of nonlinear observers for which a quadratic Lyapunov function is used to prove stability.

Domaines: Automatique / Robotique

Daniele Astolfi, Pauline Bernard, Romain Postoyan, Lorenzo Marconi. Redesign of discrete-time nonlinear observers with state estimate constraints guaranteed in prescribed convex set. 11th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2019, Sep 2019, Vienna, Austria. ⟨hal-02411361⟩