Data-Driven Aperiodic Sampled-Data Control of Markovian Jump System
研究了马尔可夫跳跃系统在非周期采样数据控制下的数据驱动控制问题，通过构建环状李雅普诺夫泛函建立稳定性条件，并基于数据设计控制器，用飞机系统模型验证了有效性。
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.