7 papers
Data-Driven Co-Design of Event-Triggered and Sparse Control for Resource-Aware Networked Control Systems
Zhaohua Yang, Xiaoxu Lyu, Dawei Shi +1
This paper investigates the data-driven co-design of event-triggered control (ETC) and sparse control (SC) for networked control systems (NCSs) with unknown linear dynamics. While…
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…
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_…
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…
Performance Analysis of Distributed Filtering under Mismatched Noise Covariances
Xiaoxu Lyu, Guanghui Wen, Ling Shi +2
This paper systematically investigates the performance of consensus-based distributed filtering under mismatched noise covariances. First, we introduce three performance evaluation…
Distributed State Estimation for Discrete-Time Linear Systems over Directed Graphs: A Measurement Perspective
Xiaoxu Lyu, Guanghui Wen, Yuezu Lv +2
This paper proposes a novel consensus-based distributed filter over directed graphs under the collectively observability condition. The distributed filter is designed using an augm…
On the Effects of Modeling Errors on Distributed Continuous-time Filtering
Xiaoxu Lyu, Shilei Li, Dawei Shi +1
This paper offers a comprehensive performance analysis of the distributed continuous-time filtering in the presence of modeling errors. First, we introduce two performance indices,…