Data-Driven Aperiodic Sampled-Data Control of Markovian Jump System

In this article, the problem of data-driven control for Markovian jump systems (MJSs) under aperiodic sampled-data (ASD) control is studied. By constructing a loop-based Lyapunov functional (LBLF), the stability criterion of MJSs based on the model is established. Combining this model-based condition with data-based representations, two distinct stability conditions are formulated. ASD controllers are subsequently designed based on these conditions. The proposed approach is validated by modeling an aircraft system as an MJS, with flight test data showing that the controller effectively stabilizes the system, whether the system matrices are known or unknown. Furthermore, a numerical example highlights that the proposed approach achieves a larger upper bound for the sampled-data period.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Systems Man and Cybernetics Systems
Published
2025-02-21
DOI
https://doi.org/10.1109/tsmc.2025.3540568
Citations
5
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
6.07

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Data-Driven Aperiodic Sampled-Data Control of Markovian Jump System

Jianwei Xia, Ju H. Park, Xiangpeng Xie, Linqi Wang et al.
5 citations
IEEE Transactions on Systems Man and Cybernetics Systems
Fault Detection and Control Systems
6.07
article

Data-Driven Aperiodic Sampled-Data Control of Markovian Jump System

Jianwei Xia, Ju H. Park, Xiangpeng Xie, Linqi Wang, Guoliang Chen
article en
5 citations

Abstract

In this article, the problem of data-driven control for Markovian jump systems (MJSs) under aperiodic sampled-data (ASD) control is studied. By constructing a loop-based Lyapunov functional (LBLF), the stability criterion of MJSs based on the model is established. Combining this model-based condition with data-based representations, two distinct stability conditions are formulated. ASD controllers are subsequently designed based on these conditions. The proposed approach is validated by modeling an aircraft system as an MJS, with flight test data showing that the controller effectively stabilizes the system, whether the system matrices are known or unknown. Furthermore, a numerical example highlights that the proposed approach achieves a larger upper bound for the sampled-data period.

IEEE Transactions on Systems Man and Cybernetics SystemsVol. 55(5)
Liaocheng University (CN), Nanjing University of Posts and Telecommunications (CN), Yeungnam University (KR)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province
Reduced inequalities
Openalex Percentile: Top 4%
Fault Detection and Control Systems
6.07
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.