PID2018 Benchmark Challenge: learning feedforward control

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dc.authoridChen, YangQuan/0000-0002-7422-5988
dc.authoridATES, Abdullah/0000-0002-4236-6794
dc.authorwosidLi, Yan/K-7292-2012
dc.authorwosidYuan, Jie/AAD-1604-2019
dc.authorwosidChen, YangQuan/A-2301-2008
dc.authorwosidATES, Abdullah/V-6929-2018
dc.contributor.authorZhao, Yang
dc.contributor.authorDehghan, Sina
dc.contributor.authorAtes, Abdullah
dc.contributor.authorYuan, Jie
dc.contributor.authorZhou, Fengyu
dc.contributor.authorLi, Yan
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.abstractThe design and application of learning feedforward controllers (LFFC) for the one staged refrigeration cycle model described in the PID2018 Benchmark Challenge is presented, and its effectiveness is evaluated. The control system consists of two components: 1) a preset PID component and 2) a learning feedforward component which is a function approximator that is adapted on the basis of the feedback signal. A B-spline network based LFFC and a low-pass filter based LFFC are designed to track the desired outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet. Encouraging simulation results are included. Qualitative and quantitative comparison results evaluations show that, with little effort, a high-performance control system can be obtained with this approach. Our initial simple attempt of low-pass filter based LFFC and B-spline network based LFFC give J=0.4902 and J=0.6536 relative to the decentralized PID controller, respectively. Besides, the initial attempt of a combination controller of our optimized PI controller and low-pass filter LFFC gives J=0.6947 relative to the multi-variable PID controller. (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.sponsorshipNational Natural Science Foundation of China [61375084, 61773242]; Key Program of Natural Science Foundation of Shandong Province [ZR2015QZ08]; Key Program of Scientific and Technological Innovation of Shandong Province [2017CXGC0926]; Key Research and Development Program of Shandong Province [2017GGX30133]; National Key Research and Development Program of China [2017YFB1302400]en_US
dc.description.sponsorshipThe first author wishes to thank the members of PTUC SIG (Precision Temperature Uniformity Control Special Interest Group) at UC Merced MESA Lab 1 for fruitful discussions and productive meetings. Project supported by National Natural Science Foundation of China (Grant No. 61375084 and Grant No. 61773242), Key Program of Natural Science Foundation of Shandong Province (Grant No. ZR2015QZ08), Key Program of Scientific and Technological Innovation of Shandong Province (Grand No. 2017CXGC0926), Key Research and Development Program of Shandong Province (Grant No. 2017GGX30133), The National Key Research and Development Program of China (Grant No. 2017YFB1302400).en_US
dc.identifier.doi10.1016/j.ifacol.2018.06.175
dc.identifier.endpage668en_US
dc.identifier.issn2405-8963
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85048794308en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage663en_US
dc.identifier.urihttps://doi.org/10.1016/j.ifacol.2018.06.175
dc.identifier.urihttps://hdl.handle.net/11616/98351
dc.identifier.volume51en_US
dc.identifier.wosWOS:000435709300114en_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.subjectLearning feedforward controlen_US
dc.subjectvapour-compression refrigeration systemen_US
dc.subjectconditional integrationen_US
dc.subjectPID 2018 Benchmark Challengeen_US
dc.titlePID2018 Benchmark Challenge: learning feedforward controlen_US
dc.typeConference Objecten_US

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