Implementation of a New Neural Network Function Block to Programmable Logic Controllers Library Function

Main Authors: Hamid Abdi, Abolfazl Salami, Abolfazl Ahmadi
Format: Article Journal
Bahasa: eng
Terbitan: , 2007
Subjects:
Online Access: https://zenodo.org/record/1062844
ctrlnum 1062844
fullrecord <?xml version="1.0"?> <dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Hamid Abdi</creator><creator>Abolfazl Salami</creator><creator>Abolfazl Ahmadi</creator><date>2007-05-21</date><description>Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.</description><identifier>https://zenodo.org/record/1062844</identifier><identifier>10.5281/zenodo.1062844</identifier><identifier>oai:zenodo.org:1062844</identifier><language>eng</language><relation>doi:10.5281/zenodo.1062843</relation><relation>url:https://zenodo.org/communities/waset</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/4.0/legalcode</rights><subject>Programmable Logic Controller</subject><subject>PLC Programming</subject><subject>Neural Networks</subject><subject>Perception Network</subject><subject>Intelligent Control.</subject><title>Implementation of a New Neural Network Function Block to Programmable Logic Controllers Library Function</title><type>Journal:Article</type><type>Journal:Article</type><recordID>1062844</recordID></dc>
language eng
format Journal:Article
Journal
Journal:Journal
author Hamid Abdi
Abolfazl Salami
Abolfazl Ahmadi
title Implementation of a New Neural Network Function Block to Programmable Logic Controllers Library Function
publishDate 2007
topic Programmable Logic Controller
PLC Programming
Neural Networks
Perception Network
Intelligent Control
url https://zenodo.org/record/1062844
contents Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.
id IOS16997.1062844
institution ZAIN Publications
institution_id 7213
institution_type library:special
library
library Cognizance Journal of Multidisciplinary Studies
library_id 5267
collection Cognizance Journal of Multidisciplinary Studies
repository_id 16997
subject_area Multidisciplinary
city Stockholm
province INTERNASIONAL
shared_to_ipusnas_str 1
repoId IOS16997
first_indexed 2022-06-06T04:41:47Z
last_indexed 2022-06-06T04:41:47Z
recordtype dc
_version_ 1734902840744214528
score 17.538404