NDLI: Estimation of the Non-Measurable State Variables of a Transcutaneous Energy Transmission System for Artificial Human Implants Using Extended Kalman Filters

Content Provider	Springer Nature Link
Author	Liu, Wei Tang, Houjun Fang, Wan Ye, Pengsheng
Copyright Year	2009
Abstract	Due to the separation of the two sides of the coupling network, the acquisition of data on the operating state variables of a transcutaneous energy transmission system (TETS) inside the human body is difficult. A non-measurable state estimation approach is used in this work to facilitate the estimation of non-measurable variables on the secondary side of the TETS, including the current of the secondary coil and the output voltage of the secondary side. The estimation algorithm is based on a discrete dynamic mathematical model of the TETS. Following this model, using the extended Kalman filter (EKF) algorithm, the complexity of the TETS for artificial human implants can be reduced, while the reliability is simultaneously enhanced. Additionally, as an adaptive filter, the EKF can also successfully filter out processing noise during energy transmission. All of the results are verified by simulation using MATLAB.
Starting Page	581
Ending Page	593
Page Count	13
File Format	PDF
ISSN	0278081X
Journal	Circuits, Systems, and Signal Processing
Volume Number	28
Issue Number	4
e-ISSN	15315878
Language	English
Publisher	SP Birkhäuser Verlag Boston
Publisher Date	2009-03-24
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Non-measurable state variables Transcutaneous energy transmission system Artificial human implants Extended Kalman filter Estimator Electronics and Microelectronics, Instrumentation Signal, Image and Speech Processing Electrical Engineering Circuits and Systems
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing

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