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.
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页码：385 / 388
页数：4
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