Application of artificial neural-network to control the light of multi-color LED system

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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Detail(s)

Original languageEnglish
Title of host publication2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages3669-3675
ISBN (electronic)978-1-5090-2998-3
Publication statusPublished - Oct 2017

Conference

Title9th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2017
LocationDuke Energy Convention Center
PlaceUnited States
CityCincinnati
Period1 - 5 October 2017

Link(s)

DOI

DOI
Check@CityULib
Link to Scopus https://www.scopus.com/record/display.uri?eid=2-s2.0-85041488629&origin=recordpage
Permanent Link https://scholars.cityu.edu.hk/en/publications/publication(74db8069-dc45-4dd6-a490-dd0c20bb5b8b).html

Abstract

This paper presents the application of artificial neural-network (ANN) algorithm to control the light of multicolor light-emitting-diode (LED) system. Compared with conventional control methods, the proposed method has the merits of 1) not requiring an accurate system model, 2) achieving quality lighting with higher color rendering index (CRI), 3) requiring only one red-green-blue (RGB) color sensor for feedback, and 4) handling the change of flux, shift of wavelength with temperature and aging. The proposed method is introduced based on a buck-type single-inductor-multiple-output (SIMO) LED driver with channels connected in series. A prototype has been built and experimental results are given.

Research Area(s)

  • ANN, CRI, Lighting control, RGBA, SIMO power conversion

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Publication fingerprints text

100
Artificial Neural N... Computer Science
100
Light-Emitting Diod... Computer Science
33
Experimental Result Computer Science
33
Control Method Computer Science
33
Network Algorithm Computer Science
33
Model System Engineering
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Citation Format(s)

[ RIS ] [ BibTeX ]
Application of artificial neural-network to control the light of multi-color LED system. / Zhan, Xiaoqing; Wang, Wenguan; Chung, Henry Shu-hung.
2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017. Institute of Electrical and Electronics Engineers, Inc., 2017. p. 3669-3675 8096650.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review