Lnu-fuzzy network as a mathematical adaptive model of a hydraulic system
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F18%3A00364852" target="_blank" >RIV/68407700:21220/18:00364852 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.17973/MMSJ.2018_11_201856" target="_blank" >https://doi.org/10.17973/MMSJ.2018_11_201856</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.17973/MMSJ.2018_11_201856" target="_blank" >10.17973/MMSJ.2018_11_201856</a>
Alternative languages
Result language
angličtina
Original language name
Lnu-fuzzy network as a mathematical adaptive model of a hydraulic system
Original language description
Model adaptive controllers such as Model Predictive Control or Model Reference Adaptive Control need a precise mathematical model of the controlled system adaptable in real-time. Systems consisting of a hydraulic 4- way proportional valve and a linear motor have non-linear behaviour such as hysteresis of and valve, death zone of a valve spool, time delay of a data transfer and control unit, dependence on coils temperature and oil temperature and nonlinear flow characteristics. This paper introduces modified Neuro-Fuzzy network as a mathematical adaptive model of a hydraulic system with above mentioned properties. The paper presents the basic architecture of Neuro-Fuzzy network which consists of artificial neural units a fuzzy layer and introduces modifications focused on identification. The basic real-time learning method such as Normalized Gradient Descent is introduced specially for the designed Neuro-Fuzzy Network. Identification and real time learning abilities of the model were tested on the hydraulic stand.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
MM Science Journal
ISSN
1803-1269
e-ISSN
1805-0476
Volume of the periodical
2018
Issue of the periodical within the volume
November
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
4
Pages from-to
2573-2576
UT code for WoS article
000532566800016
EID of the result in the Scopus database
2-s2.0-85057331148