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

作者：Guoliang Chen, Linqi Wang, Jianwei Xia, Xiangpeng Xie, Ju H. Park · 发表于：IEEE Transactions on Systems Man and Cybernetics Systems · 年份：2025 · DOI：10.1109/tsmc.2025.3540568 · 被引用次数：11 · 研究领域：Fault Detection and Control Systems、Fuzzy Logic and Control Systems、Neural Networks and Applications

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.