Reduced-Order Observer Based-Fault Estimation for Markovian Jump Systems With Time-Varying Generally Uncertain Transition Rates

Reduced-Order Observer Based-Fault Estimation for Markovian Jump Systems With Time-Varying Generally Uncertain Transition Rates
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基于降阶观测器的具有时变一般不确定转移率的马尔可夫跳跃系统的故障估计

DOI:
10.1109/tcsi.2020.2982968
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发表时间:
2020-04
影响因子:
5.1
通讯作者:
Xiaohang Li
Xiaohang Li
中科院分区:
工程技术2区
文献类型:
--
作者:
Dunke Lu;Xiaohang Li

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本文解决了同时估计一类马尔可夫跳跃系统的执行器故障、输出干扰和传感器故障的问题,该系统具有时变且通常不确定的转换率。为了进行故障估计,提出了一种新的降阶观测器,其增益矩阵被设计为完全解耦系统的未知输入。对于时变的一般不确定的转移率的解决方案,开发了离线量化机制,这可以在很大程度上帮助证明观察者误差系统是稳定的。尽管存在外部干扰和时变随机切换,所提出的方法仍能够保证状态和故障的准确估计。此外,通过数值算例验证了所设计的故障估计方法的正确性。
This paper addresses such problem for simultaneous estimations of the actuator fault, output disturbance and sensor fault for a type of Markovian jump systems, which takes on time-varying generally uncertain transition rates. In order to perform estimations for faults, a new reduced-order observer is proposed, of which the gain matrix is designed to fully decouple the unknown input for the system. As for the solution to time-varying generally uncertain transition rates, an offline quantization mechanism is developed, which can help to prove, to a large extent, the observer error system to be stable. The proposed method is able to guarantee the exact estimations of the states and faults in spite of the existence of external disturbances and the time-varying stochastic switching. Furthermore, a numerical example is brought to testify the correctness of the designed fault estimation method.
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发表时间: 2018-05
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