Publication
On state-estimation in weakly-observable scenarios and implicitly regularized observers
Conference Article
Conference
IEEE Conference on Decision and Control (CDC)
Edition
60th
Pages
3996-4001
Doc link
https://doi.org/10.1109/CDC45484.2021.9682914
File
Abstract
This work proposes a framework to design observers for systems that present low observability. It is shown that, in these scenarios, the estimation problem becomes ill-posed, which drastically limits the performance of standard observers, specially in the presence of noise. Consequently, this paper presents a method to design an observer that optimizes some potential function to be defined by the designer. This allows to implicitly regularize the estimation and recover a well-posed problem. The proposed technique is validated in a set of weakly-observable systems and the performance is compared with a common Kalman filter-like observer.
Categories
control theory, observability.
Author keywords
linear observers
Scientific reference
A. Cecilia and R. Costa. On state-estimation in weakly-observable scenarios and implicitly regularized observers, 60th IEEE Conference on Decision and Control, 2021, Austin, TX, USA (Virtual), pp. 3996-4001.
Follow us!