PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System

INTRODUCTION: Preservation of fruits by drying is one of the general and important traditional technique followed by the process industries. An accurate controller of relative humidity and temperature is required for the fruit drying control system, which determines the qua...

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Autores principales:	Priya Krishnan, Remya Gopalakrishnan, R. Nishanth, Abin Joseph, Agath Martin, Nidhin Sani
Formato:	article
Lenguaje:	EN
Publicado:	European Alliance for Innovation (EAI) 2021
Materias:	fruit drying adaptive neuro fuzzy inference system (anfis) propositional-integral-derivative (pid) controller particle swarm optimization (pso) fuzzy logic controller (flc) Science Q Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/933999083e5d4ad09bd9f7fb07701eac
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spelling	oai:doaj.org-article:933999083e5d4ad09bd9f7fb07701eac2021-11-30T11:07:23ZPSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System2032-944X10.4108/eai.9-3-2021.168961https://doaj.org/article/933999083e5d4ad09bd9f7fb07701eac2021-11-01T00:00:00Zhttps://eudl.eu/pdf/10.4108/eai.9-3-2021.168961https://doaj.org/toc/2032-944XINTRODUCTION: Preservation of fruits by drying is one of the general and important traditional technique followed by the process industries. An accurate controller of relative humidity and temperature is required for the fruit drying control system, which determines the quality of the dried fruits.OBJECTIVES: To design optimal Propositional-Integral-Derivative (PID) controller based on the Particle Swarm Optimization and Radial Basis Functional Neural Network (PSO-RBFNN) for pineapple drying system.METHODS: A Propositional-Integral-Derivative (PID) controller based on the Particle Swarm Optimization and Radial Basis Functional Neural Network ( PSO-RBFNN) was proposed in this paper for pineapple drying system. Also, the coupling relationship of relative humidity and temperature is more complicated due to the fluctuations and non-linearity in the drying system. An intelligent Adaptive Neuro Fuzzy Inference System (ANFIS) coupling model is utilized in this paper to access the coupling relationship between relative humidity and temperature.RESULTS: The proposed control system has been implemented in the MATLAB and results are compared with PID controller, Fuzzy Logic Controller (FLC) and Fuzzy PID controller for the performance constraints such as settling time, peak over shoot and steady state error.CONCLUSION: The proposed PSO-RBFNN based PID controller gives better control performance with the highly minimized settling time (42 sec for humidity and 40 sec for temperature) and completely eliminated steady state error and Peak overshoot. Finally, the PSO-RBFNN algorithm based PID controller is concluded as the e ffective system.Priya KrishnanRemya GopalakrishnanR. NishanthAbin JosephAgath MartinNidhin SaniEuropean Alliance for Innovation (EAI)articlefruit dryingadaptive neuro fuzzy inference system (anfis)propositional-integral-derivative (pid) controllerparticle swarm optimization (pso)fuzzy logic controller (flc)ScienceQMathematicsQA1-939Electronic computers. Computer scienceQA75.5-76.95ENEAI Endorsed Transactions on Energy Web, Vol 8, Iss 36 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	fruit drying adaptive neuro fuzzy inference system (anfis) propositional-integral-derivative (pid) controller particle swarm optimization (pso) fuzzy logic controller (flc) Science Q Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95
spellingShingle	fruit drying adaptive neuro fuzzy inference system (anfis) propositional-integral-derivative (pid) controller particle swarm optimization (pso) fuzzy logic controller (flc) Science Q Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95 Priya Krishnan Remya Gopalakrishnan R. Nishanth Abin Joseph Agath Martin Nidhin Sani PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System
description	INTRODUCTION: Preservation of fruits by drying is one of the general and important traditional technique followed by the process industries. An accurate controller of relative humidity and temperature is required for the fruit drying control system, which determines the quality of the dried fruits.OBJECTIVES: To design optimal Propositional-Integral-Derivative (PID) controller based on the Particle Swarm Optimization and Radial Basis Functional Neural Network (PSO-RBFNN) for pineapple drying system.METHODS: A Propositional-Integral-Derivative (PID) controller based on the Particle Swarm Optimization and Radial Basis Functional Neural Network ( PSO-RBFNN) was proposed in this paper for pineapple drying system. Also, the coupling relationship of relative humidity and temperature is more complicated due to the fluctuations and non-linearity in the drying system. An intelligent Adaptive Neuro Fuzzy Inference System (ANFIS) coupling model is utilized in this paper to access the coupling relationship between relative humidity and temperature.RESULTS: The proposed control system has been implemented in the MATLAB and results are compared with PID controller, Fuzzy Logic Controller (FLC) and Fuzzy PID controller for the performance constraints such as settling time, peak over shoot and steady state error.CONCLUSION: The proposed PSO-RBFNN based PID controller gives better control performance with the highly minimized settling time (42 sec for humidity and 40 sec for temperature) and completely eliminated steady state error and Peak overshoot. Finally, the PSO-RBFNN algorithm based PID controller is concluded as the e ffective system.
format	article
author	Priya Krishnan Remya Gopalakrishnan R. Nishanth Abin Joseph Agath Martin Nidhin Sani
author_facet	Priya Krishnan Remya Gopalakrishnan R. Nishanth Abin Joseph Agath Martin Nidhin Sani
author_sort	Priya Krishnan
title	PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System
title_short	PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System
title_full	PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System
title_fullStr	PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System
title_full_unstemmed	PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System
title_sort	pso-rbfnn based optimal pid controller and anfis based coupling for fruits drying system
publisher	European Alliance for Innovation (EAI)
publishDate	2021
url	https://doaj.org/article/933999083e5d4ad09bd9f7fb07701eac
work_keys_str_mv	AT priyakrishnan psorbfnnbasedoptimalpidcontrollerandanfisbasedcouplingforfruitsdryingsystem AT remyagopalakrishnan psorbfnnbasedoptimalpidcontrollerandanfisbasedcouplingforfruitsdryingsystem AT rnishanth psorbfnnbasedoptimalpidcontrollerandanfisbasedcouplingforfruitsdryingsystem AT abinjoseph psorbfnnbasedoptimalpidcontrollerandanfisbasedcouplingforfruitsdryingsystem AT agathmartin psorbfnnbasedoptimalpidcontrollerandanfisbasedcouplingforfruitsdryingsystem AT nidhinsani psorbfnnbasedoptimalpidcontrollerandanfisbasedcouplingforfruitsdryingsystem
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PSO-RBFNN Based Optimal PID Controller and ANFIS Based Coupling for Fruits Drying System

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