3 papers
eess.SY2025
An Autocovariance Least-Squares-Based Data-Driven Kalman Filter for Unknown Systems
Suyang Hu, Xiaoxu Lyu, Peihu Duan +2
This article investigates the problem of data-driven state estimation for linear systems with both unknown system dynamics and noise covariances. We propose an Autocovariance Least…
math.OC2025
Data-Driven Structured Controller Design Using the Matrix S-Procedure
Zhaohua Yang, Yuxing Zhong, Nachuan Yang +2
This paper focuses on the data-driven optimal structured controller design for discrete-time linear time-invariant (LTI) systems, considering both the performance and the $H_…
eess.SP2024
Bias-VarianceTrade-off in Kalman Filter-Based Disturbance Observers
Shilei Li, Dawei Shi, Xiaoxu Lyu +2
The performance of disturbance observers is strongly influenced by the level of prior knowledge about the disturbance model. The simultaneous input and state estimation (SISE) algo…