High-Gain Dead-Zone Observers for Linear and Nonlinear Plants

M. Cocetti (1, 2) , Sophie Tarbouriech (3) , Luca Zaccarian (4, 3)

1 UNITN - Università degli Studi di Trento = University of Trento
2 LAAS - Laboratoire d'analyse et d'architecture des systèmes
3 LAAS-MAC - Équipe Méthodes et Algorithmes en Commande
4 Dipartimento di Ingegneria Industriale [Trento]

We propose an adaptive dead-zone mechanism to robustify observers against high-frequency noise. The construction applies to Luenberger observers and high-gain observers for plants in strict feedback form. The dead-zone improves performances by trimming a portion of the output injection term and trapping the high frequency noise in the dead band. We show that the observer gain and the adaptation parameters can be obtained by solving a linear matrix inequality, whose feasibility only requires detectability of the plant. The parameters obtained through this optimization ensure (in the absence of noise) global exponential stability of the estimation error dynamics, and input-to-state stability (ISS) from the measurement noise to the estimation error.

Mots clés: Observers for Linear systems; Adaptive systems; Filtering; LMIs; Lyapunov methods

Domaines: Automatique / Robotique

M. Cocetti, Sophie Tarbouriech, Luca Zaccarian. High-Gain Dead-Zone Observers for Linear and Nonlinear Plants. IEEE Control Systems Letters, 2019, 3 (2), pp.356-361. ⟨10.1109/LCSYS.2018.2880931⟩. ⟨hal-01970882⟩