New paper on IEEE Control Systems Letters!
© 2021 EPFL
Our paper "Data-driven Unknown-input Observers and State Estimation" has been published on the IEEE Control System Letters (L-CSS). The article can be found here.
Unknown-input observers (UIOs) enable state estimation when some inputs of a system are not known. Without requiring the knowledge of unknown inputs or a system model, we provide data-driven conditions for the existence of a UIO. We also provide a novel method based on data for obtaining state estimates, which, under the existence conditions, are guaranteed to converge to the true system state. Moreover, the proposed method is also suitable for standard state estimation. This paper is the first work on data-driven unknown-input state estimation.