publication . Article . 2013

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

Khulood A. Dagher; Ahmed S. Al-Araji;
Open Access English
  • Published: 01 Dec 2013 Journal: Al-Khawarizmi Engineering Journal (issn: 1818-1171, eissn: 2312-0789, Copyright policy)
  • Publisher: Al-Khwarizmi College of Engineering – University of Baghdad
Abstract
 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 dy...
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Subjects
arXiv: Computer Science::Neural and Evolutionary Computation
ACM Computing Classification System: MathematicsofComputing_NUMERICALANALYSIS
free text keywords: Particle Swarm Optimization, PID Controller, Neural Network, CSTR, Chemical engineering, TP155-156, Engineering (General). Civil engineering (General), TA1-2040
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Al-Khawarizmi Engineering Journal
Article . 2013
Provider: DOAJ-Articles
Al-Khawarizmi Engineering Journal
Article . 2013
Provider: DOAJ-Articles
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