NDLI: Use of an artificial neural network for current derivative estimation

Content Provider	IEEE Xplore Digital Library
Author	Hind, D. Sumner, M. Gerada, C.
Copyright Year	2013
Description	Author affiliation: Univ. of NOTTINGHAM, Nottingham, UK (Hind, D.; Sumner, M.; Gerada, C.)
Abstract	The Fundamental PWM technique for saliency tracking based sensorless (encoderless) motor control uses current derivative measurements to calculate the rotor position. However parasitic impedances in the drive, motor and cabling cause high frequency oscillations in the current, when the inverter's IGBTs switch. This prevents the immediate measurement of the current derivative when a new voltage is imposed on the motor and has led to an enforced minimum PWM vector time restriction that allows the oscillations in the current response to decay sufficiently before current derivative measurements are made. In this work a new method is proposed to reduce this minimum PWM vector time restriction by estimating the current derivative in the presence of such oscillations using a neural network. Training of the neural network is performed off-line with the neural network configuration (weights and biases) being stored on removable storage media. This can reduce the training burden by allowing network configurations to be saved and recalled, potentially offering a “plug and play” solution for previously encountered drive setups. An additional benefit of the proposed solution is that the current derivative is estimated from data captured using standard industrial current sensors instead of dedicated current derivative sensors. The proposed method and its implementation are discussed and on-line experimental results are presented which validate the feasibility and performance of the proposed technique.
Starting Page	1
Ending Page	10
File Size	713510
Page Count	10
File Format	PDF
ISBN	9781479901166
DOI	10.1109/EPE.2013.6634327
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-02
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Field Programmable Gate Array (FPGA) Current measurement Parasitics Artificial neural networks Sensorless control Vectors Sensors Neural network Self-sensing control Transient analysis Field programmable gate arrays Oscillators
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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