Zhang Xiang, Wang Hai, Song Jun, He Shuping, Sun Changyin
IEEE Trans Cybern. 2023 Aug;53(8):5059-5068. doi: 10.1109/TCYB.2022.3170110. Epub 2023 Jul 18.
This article investigates the co-design problem of adaptive event-triggered schemes (AETSs) and asynchronous fault detection filter (AFDF) for nonhomogeneous higher-level Markov jump systems, involving the hidden Markov model (HMM), higher-level Markov chain (MC), and conic-type nonlinearities. The transformation of the system transition probability can be reflected by the designed higher-level MC. An HMM with another conditional transition probability is applied to detect higher-level Markov processes and make the system be more practical. In order to balance the utilization of network resources and system performance, a novel AETS is proposed and used in the construction of the AFDF. By the Lyapunov theory, sufficient conditions are given to ensure the existences of the AETS and AFDF. It is not only an appropriate tradeoff between the utilization of network resources and system performance, but also reduces the conservatism. Finally, a numerical example is given to detect the faults effectively by the co-designed AFDF.
本文研究了非齐次高阶马尔可夫跳跃系统的自适应事件触发方案（AETSs）与异步故障检测滤波器（AFDF）的协同设计问题，涉及隐马尔可夫模型（HMM）、高阶马尔可夫链（MC）和圆锥型非线性。所设计的高阶MC能够反映系统转移概率的变化。应用具有另一种条件转移概率的HMM来检测高阶马尔可夫过程，使系统更具实用性。为了平衡网络资源利用与系统性能，提出了一种新颖的AETS并将其用于AFDF的构建。利用李雅普诺夫理论，给出了确保AETS和AFDF存在的充分条件。这不仅在网络资源利用与系统性能之间进行了恰当的权衡，还降低了保守性。最后，给出了一个数值例子，以说明协同设计的AFDF能够有效地检测故障。
