Fault diagnosis of a nonlinear hybrid system using adaptive unscented Kalman filter bank

被引：0
|
作者：
Chandrani Sadhukhan
Swarup Kumar Mitra
Mrinal Kanti Naskar
Mohsen Sharifpur
机构：
[1] MCKV Institute of Engineering,Electrical Engineering Department
[2] MCKV Institute of Engineering,Electronic and Telecommunication Engineering Department
[3] Jadavpur University,Electronic and Telecommunication Engineering Department
[4] University of Pretoria,Department of Mechanical and Aeronautical Engineering
[5] Duy Tan University,Institute of Research and Development
来源：
Engineering with Computers | 2022年 / 38卷
关键词：
Model-based fault diagnosis; Adaptive unscented Kalman filter (AUKF); Adaptive extended Kalman filter (AEKF); Residual signal; Discrete mode;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a model-based fault diagnosis scheme of a nonlinear hybrid system using an adaptive unscented Kalman filter (AUKF) bank is proposed. The hybrid system is an amalgamation of discrete dynamics and continuous states. Fault diagnosis for simultaneous occurrences of multiple faults such as leakage fault, clogging fault, sensor fault, and actuator fault on a benchmark three-tank system are simulated. The residual signal based output generates some discrete modes that guarantee the uniqueness of the concerning fault. The efficacy of the proposed scheme is compared with that of the adaptive extended Kalman filter (AEKF) bank on the same system to prove its better response over AEKF.
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页码：2717 / 2728
页数：11
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