| Robust fault diagnosis for non-Gaussian stochastic systems based on the rational square-root approximation model |
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| 基金项目： | Supported by the National Natural Science Foundation of China （Grant No. 60534010） and the Outstanding Overseas Chinese Scholars Fund of CAS （Grant No. 2004-1-4） |
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| 摘 要： | The task of robust fault detection and diagnosis of stochastic distribution control （SDC） systems with uncertainties is to use the measured input and the system output PDFs to still obtain possible faults information of the system. Using the rational square-root B-spline model to represent the dynamics between the output PDF and the input, in this paper, a robust nonlinear adaptive observer-based fault diagnosis algorithm is presented to diagnose the fault in the dynamic part of such systems with model uncertainties. When certain conditions are satisfied, the weight vector of the rational square-root B-spline model proves to be bounded. Conver- gency analysis is performed for the error dynamic system raised from robust fault detection and fault diagnosis phase. Computer simulations are given to demon- strate the effectiveness of the proposed algorithm.
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| 关 键 词： | 鲁棒误差诊断 非高斯随机系统 平方根逼近模型 随机分布控制 |
Robust fault diagnosis for non-Gaussian stochastic systems based on the rational square-root approximation model |
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| Authors: | LiNa Yao Hong Wang |
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| Affiliation: | (1) School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China;(2) Control Systems Centre, University of Manchester, Manchester, M60 1QD, UK;(3) Institute of Automation, Chinese Academy of Sciences, Beijing, 100080, China |
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| Abstract: | The task of robust fault detection and diagnosis of stochastic distribution control(SDC) systems with uncertainties is to use the measured input and the system output PDFs to still obtain possible faults information of the system. Using the rational square-root B-spline model to represent the dynamics between the output PDF and the input,in this paper,a robust nonlinear adaptive observer-based fault diagnosis algorithm is presented to diagnose the fault in the dynamic part of such systems with model uncertainties. When certain conditions are satisfied,the weight vector of the rational square-root B-spline model proves to be bounded. Convergency analysis is performed for the error dynamic system raised from robust fault detection and fault diagnosis phase. Computer simulations are given to demonstrate the effectiveness of the proposed algorithm. |
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| Keywords: | SDC systems output probability density functions(PDFs) robust fault detection and diagnosis rational square-root B-spline functions |
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