Fault Detection and Diagnosis for Non-Gaussian Singular Stochastic Distribution Systems

被引：0

作者：

Jing, Shi ^{[1
]}

Yi, Qu ^{[1
]}

Peng, Du ^{[2
]}

机构：

[1] Xianyang Vocat Tech Coll, Dept Elect & Informat Engn, Xianyang, Peoples R China

[2] Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou, Peoples R China

来源：

PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON MECHATRONICS, ELECTRONIC, INDUSTRIAL AND CONTROL ENGINEERING | 2015年 / 8卷

关键词：

probability density fuctions; singuktr stochastic distribution; controljault detection; diagnosis;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Fault detection and diagnosis (FDD) for singular stochastic distribution control (SDC) systems via the output probability density functions(PDFs) have been discussed. The PDFs can be approximated via square-root B-spline expansion,and expansions to represent the dynamics weighting systems between the system input and output PDFs. an novel fault detection and diagnosis algorithm is presented using the parameter-updating. Finally, the simulation result is included to show that satisfactory robustness and closed-loop performance can be achieved.

引用

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页码：385 / 388

页数：4

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