PID2018 Benchmark Challenge: Multi-Objective Stochastic Optimization Algorithm

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dc.authoridChen, YangQuan/0000-0002-7422-5988
dc.authoridATES, Abdullah/0000-0002-4236-6794
dc.authoridYeroglu, Celaleddin/0000-0002-6106-2374
dc.authorwosidYeroglu, Celaleddin/ABG-9572-2020
dc.authorwosidChen, YangQuan/A-2301-2008
dc.authorwosidYuan, Jie/AAD-1604-2019
dc.authorwosidATES, Abdullah/V-6929-2018
dc.contributor.authorAtes, Abdullah
dc.contributor.authorYuan, Jie
dc.contributor.authorDehghan, Sina
dc.contributor.authorZhao, Yang
dc.contributor.authorYeroglu, Celaleddin
dc.contributor.authorChen, YangQuan
dc.date.accessioned2024-08-04T20:44:36Z
dc.date.available2024-08-04T20:44:36Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.description3rd IFAC Conference on Advances in Proportional-Integral-Derivative Control (PID) -- MAY 09-11, 2018 -- Ghent Univ, Ghent, BELGIUMen_US
dc.description.abstractThis paper presents a multi-objective stochastic optimization method for tuning of the controller parameters of Refrigeration Systems based on Vapour Compression. Stochastic Multi Parameter Divergence Optimization (SMDO) algorithm is modified for minimization of the Multi Objective function for optimization process. System control performance is improved by tuning of the PI controller parameters according to discrete time model of the refrigeration system with multi objective function by adding conditional integral structure that is preferred to reduce the steady state error of the system. Simulations are compared with existing results via many graphical and numerical solutions. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipInt Federat Automat Control, Tech Comm Control Design 2 1,Int Federat Automat Control, Tech Comm Proc Control 6 1,Int Federat Automat Control, Tech Comm Control Educ 9 4en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK-BIDEP) [2214/A]en_US
dc.description.sponsorshipThis study is supported by The Scientific and Technological Research Council of Turkey (TUBITAK-BIDEP) with 2214/A program number.en_US
dc.identifier.doi10.1016/j.ifacol.2018.06.113
dc.identifier.endpage881en_US
dc.identifier.issn2405-8963
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85048777235en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage877en_US
dc.identifier.urihttps://doi.org/10.1016/j.ifacol.2018.06.113
dc.identifier.urihttps://hdl.handle.net/11616/98349
dc.identifier.volume51en_US
dc.identifier.wosWOS:000435709300150en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofIfac Papersonlineen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectOptimizationen_US
dc.subjectstochasticen_US
dc.subjectSMDOen_US
dc.subjectvapour compression refrigeratoren_US
dc.subjectconditional integrationen_US
dc.titlePID2018 Benchmark Challenge: Multi-Objective Stochastic Optimization Algorithmen_US
dc.typeConference Objecten_US

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