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Fault detection for stochastic parameter-varying Markovian jump systems with application to networked control systems

机译:随机变参量马尔可夫跳跃系统的故障检测及其在网络控制系统中的应用

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This paper investigates the fault detection (FD) problem for networked control systems (NCS). The random delays from the sensor to the controller (S-C) and from the controller to the actuator (C-A) are modeled as a Markov chain. Whilst considering the data dropout phenomenon happens unavoidably and the measurement drops intermittently, C-A data dropout and S-C data dropout are coped with by introducing two independent Bernoulli processes. Based on the above two points, a stochastic parameter-varying Markovian jump system (SPVMJS) is constructed. By combining discrete Parseval theorem and strict S-procedure, a novel finite frequency approach is proposed to design an H_-/H_∞ fault detection filter for the SPVMJSs. Finally, a simulation example on the networked control system is presented to illustrate the effectiveness of the proposed method.
机译:本文研究了网络控制系统(NCS)的故障检测(FD)问题。从传感器到控制器(S-C)以及从控制器到执行器(C-A)的随机延迟被建模为马尔可夫链。在考虑不可避免地出现数据丢失现象并且测量间歇性下降的同时,通过引入两个独立的伯努利过程来解决C-A数据丢失和S-C数据丢失问题。基于以上两点,构造了一个随机的变参数马尔可夫跳跃系统(SPVMJS)。通过结合离散Parseval定理和严格的S过程,提出了一种新颖的有限频率方法来设计SPVMJS的H _ //H_∞故障检测滤波器。最后,以网络控制系统为例,说明了所提方法的有效性。

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