Safety Improvement of an Automatic Door System Using a Disturbance Observer and Neural Network

Autor:	Youngdong Yoo, Kyo-Beum Lee, Suk-Kyo Hong
Rok vydání:	2010
Předmět:	Engineering Disturbance (geology) Artificial neural network Control theory business.industry Control (management) Disturbance observer Control engineering General Medicine business
Zdroj:	The Transactions of the Korean Institute of Power Electronics. 15:401-410
ISSN:	1229-2214
DOI:	10.6113/tkpe.2010.15.5.401
Popis:	This paper proposes an automatic door system which improves the safety of conventional automatic door systems by complementing the external safety sensors. Disturbance observer using the model of automatic door system and neural network is designed. The proposed algorithm compares the observed disturbance with the output of neural network. Experimental results are presented to illustrate the feasibility of the proposed control strategy. The proposed strategy is expected to improve the safety of an automatic door system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4a2404a95666e5c8dbd8a618448d5997 https://doi.org/10.6113/tkpe.2010.15.5.401 Zobrazit plný text záznamu