Fault detection and diagnosis for non-Gaussian singular stochastic distribution systems

DOI

10.2991/meic-15.2015.89How to use a DOI?

Keywords

probability density fuctions;singular stochastic distribution;control;fault detection;diagnosis

Abstract

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jing Shi
AU  - Peng Du
AU  - Yi Qu
PY  - 2015/04
DA  - 2015/04
TI  - Fault detection and diagnosis for non-Gaussian singular stochastic distribution systems
BT  - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 385
EP  - 388
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-15.2015.89
DO  - 10.2991/meic-15.2015.89
ID  - Shi2015/04
ER  -