State Observation of LTV Systems with Delayed Measurements: A Parameter Estimation-based Approach with Fixed Convergence Time

Alexey Bobtsov (1, 2) , Nikolay Nikolaev (1) , Romeo Ortega (3, 1) , Denis Efimov (4)

1 ITMO University [Russia]
2 HDU - Hangzhou Dianzi University
3 ITAM - Instituto Tecnológico Autónomo de México
4 VALSE - Finite-time control and estimation for distributed systems

In this paper we address the problem of state observation of linear time-varying (LTV) systems with delayed measurements, which has attracted the attention of many researchers—see Sanz et al. (2019) and references therein. We show that, the parameter estimation-based observer (PEBO) design proposed in Ortega et al., 2021, Ortega et al., 2015 provides a very simple solution to the problem with reduced prior knowledge. Moreover, when PEBO is combined with the dynamic regressor extension and mixing (DREM) estimation technique (Aranovskiy et al., 2017, Ortega et al., 2019), the estimated state converges in fixed-time with extremely weak excitation assumptions.

Mots clés: Linear time-varying systems; state observer; delay systems; parameter estimation

Domaines: Automatique / Robotique

Alexey Bobtsov, Nikolay Nikolaev, Romeo Ortega, Denis Efimov. State Observation of LTV Systems with Delayed Measurements: A Parameter Estimation-based Approach with Fixed Convergence Time. Automatica, 2021, ⟨10.1016/j.automatica.2021.109674⟩. ⟨hal-03174995v2⟩