Robust sensor fault detection based on nonlinear unknown input observer

被引:85
|
作者
Zarei, Jafar [1 ]
Shokri, Ehsan [1 ]
机构
[1] Shiraz Univ Technol, Dept Elect & Elect Engn, Shiraz, Iran
关键词
Robust sensor fault detection; Unknown input observer; Cubature Kalman filter; Nonlinear systems; QUANTITATIVE MODEL; DIAGNOSIS; DESIGN; FILTER; IDENTIFICATION; SYSTEMS;
D O I
10.1016/j.measurement.2013.11.015
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Online robust sensor fault detection is a challenging problem in control engineering systems. In this paper, a new method is proposed to design a Nonlinear Unknown Input Observer (NUIO) for robust sensor fault detection. The proposed method is based on cubature rule. NUIO decouples disturbances and uncertainties from estimated states in nonlinear systems. The main contribution of this work is to exploit cubature rule in the UIO structure to overcome nonlinear calculations in the presence of external disturbances for sensor fault detection purposes. For illustrating the performance of this approach, it is applied to a nonlinear Continuous Stirred Tank Reactor (CSTR) under faulty sensors. Compared to the previous NUIO methods, which are based on Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), simulation results demonstrate the superiority of the proposed approach. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:355 / 367
页数:13
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