Neural State Estimator for Complex Mechanical Part of Electrical Drive: Neural Network Size and Performance of State Estimation

Autor:	Łuczak Dominik, Wójcik Adrian
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	two-mass drive neural network simulation studies non-linear state estimation Electronics TK7800-8360
Zdroj:	Power Electronics and Drives, Vol 3, Iss 1, Pp 205-216 (2018)
Druh dokumentu:	article
ISSN:	2451-0262 2543-4292
DOI:	10.2478/pead-2018-0017
Popis:	This paper presents the results of simulation research of an off-line-trained, feedforward neural-network-based state estimator. The investigated system is the mechanical part of an electrical drive characterised by elastic coupling with a working machine, modelled as a dual-mass system. The aim of the research was to find a set of neural network structures giving useful and repeatable results of the estimation. The mechanical resonance frequency of the system has been adopted at the level of 9.3-10.3 Hz. The selected state variables of the mechanical system are load, speed and stiffness torque of the shaft.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/5060527fadbb497fb12f28f5ab6d6d00 Zobrazit plný text záznamu View record in DOAJ