Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization

A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO techniqu...

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Autores principales:	Khulood A. Dagher, Ahmed S. Al-Araji
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2013
Materias:	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/67983fa804714254aa5176c04c50ac76
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spelling	oai:doaj.org-article:67983fa804714254aa5176c04c50ac762021-12-02T06:48:31ZDesign of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization 1818-1171https://doaj.org/article/67983fa804714254aa5176c04c50ac762013-12-01T00:00:00Zhttp://www.iasj.net/iasj?func=fulltext&aId=82638https://doaj.org/toc/1818-1171A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.Khulood A. Dagher Ahmed S. Al-Araji Al-Khwarizmi College of Engineering – University of BaghdadarticleChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 9, Iss 4, Pp 46-53 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Khulood A. Dagher Ahmed S. Al-Araji Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
description	A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
format	article
author	Khulood A. Dagher Ahmed S. Al-Araji
author_facet	Khulood A. Dagher Ahmed S. Al-Araji
author_sort	Khulood A. Dagher
title	Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
title_short	Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
title_full	Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
title_fullStr	Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
title_full_unstemmed	Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
title_sort	design of an adaptive pid neural controller for continuous stirred tank reactor based on particle swarm optimization
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2013
url	https://doaj.org/article/67983fa804714254aa5176c04c50ac76
work_keys_str_mv	AT khuloodadagher designofanadaptivepidneuralcontrollerforcontinuousstirredtankreactorbasedonparticleswarmoptimization AT ahmedsalaraji designofanadaptivepidneuralcontrollerforcontinuousstirredtankreactorbasedonparticleswarmoptimization
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Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization

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