NDLI: Extended Kalman filter training T-S fuzzy model for signal reconstruction of multifunctional sensor

Content Provider	IEEE Xplore Digital Library
Author	Guo Wei Xin Wang Jinwei Sun
Copyright Year	2009
Description	Author affiliation: Dept. of Autom. Testing & Control, Harbin Inst. of Technol., Harbin, China (Guo Wei; Xin Wang; Jinwei Sun)
Abstract	Multifunctional sensor is an emerging sensor which can measure more than one physical or chemic parameters simultaneously. But how to establish the relationship between the outputs and inputs of multifunctional sensor, which called signal reconstruction, becomes a problem. A method based on T-S fuzzy model and extended Kalman filter (EKF) for multifunctional sensor signal reconstruction is proposed in this paper. The method firstly uses subtractive clustering to partition the sampled-data and confirm the structure and initial parameters of T-S fuzzy model. Then train T-S fuzzy model with extended Kalman filter and sampled-data continuously until reaching the expected criterion. The trained T-S fuzzy model is located behind the multifunctional sensor to convert the output of the sensor into the expected parameters in the practical application. The simulation results show that the method is of higher precision and accuracy than other methods, and is very suitable for practical use.
Sponsorship	IEEE Instrum. Meas. Soc.
Starting Page	502
Ending Page	506
File Size	550638
Page Count	5
File Format	PDF
ISBN	9781424433520
ISSN	10915281
DOI	10.1109/IMTC.2009.5168501
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-05
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal reconstruction Clustering algorithms Chemical sensors Partitioning algorithms Fuzzy systems Instrumentation and measurement Fuzzy control Sun Chemical technology Automation Subtractive Clustering Multifunctional sensor Extended Kalman filter T-S fuzzy model
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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