Generalized model predictive pulse pattern control based on small-signal modelling

dc.contributor.advisorMouton, Toiten_ZA
dc.contributor.authorDorfling, Martinusen_ZA
dc.contributor.otherStellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.en_ZA
dc.date.accessioned2021-03-02T19:19:39Z
dc.date.accessioned2021-04-21T14:35:40Z
dc.date.available2021-03-02T19:19:39Z
dc.date.available2021-04-21T14:35:40Z
dc.date.issued2021-03
dc.descriptionThesis (PhD)--Stellenbosch University, 2021.en_ZA
dc.description.abstractENGLISH ABSTRACT: Optimized pulse patterns (OPPs) are a pulse-width modulation method in which the switching pattern is computed offline. Typically, the harmonic distortions for a given switching frequency are minimized. OPPs are particularly beneficial for industrial power electronic systems that operate at low switching frequencies (such as medium-voltage drive systems). However, designing a controller with a high dynamic performance for higher-order converter systems that are modulated by OPPs is a difficult and somewhat unexplored task. For first-order converter systems, a state-of-the-art industrial control technique known as model predictive pulse pattern control achieves a high dynamic performance. This thesis proposes a generalized model predictive pulse pattern controller that is applicable to (linear) higher-order converter systems. Using the notion of small-signal modelling, the dynamic equations of the state variables of the converter system are linearized around the optimal steadystate trajectory that results from the OPP. Key to the control method is to model the modifications to a pulse pattern with the strengths of impulses, resulting in the modifications to the converter states being linear in the impulse strengths. The proposed controller is formulated according to the model predictive control methodology. Thanks to the linear internal dynamic model, the underlying optimization problem can be formulated as a convex quadratic program. Simulation results demonstrate that the proposed controller achieves a very short response time during transients and superior harmonic performance during steady-state operation. Importantly, an implementation of the control algorithm on a low-cost field-programmable gate array demonstrates that the controller can execute in real-time within a short sampling interval of 25 µs; thus far, none of the (few) existing OPP-based controllers for higher-order converter systems have been proven to be practically implementable. Additionally, the control method is augmented with constraints on the state variables. Specifically, the state variables are given bounds that they should remain within. The method is verified through simulation. Furthermore, balancing of the neutral-point potential is integrated in the controller. Simulation results show that the balancing method performs well under dynamic operating conditions, including during zero power factor at the converter terminals, where traditional balancing methods tend to fail.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Geoptimeerdepulspatrone (OPPs) is ’n pulswydte-modulasiemetode waarin die skakelpatroon vanlyn bereken word. Die harmoniese distorsie van ’n gegewe skakelfrekwensie sal tipies geminimeer word. OPPs is veral voordelig vir industriële drywingselektroniese stelsels wat teen ’n lae skakelfrekwensie funksioneer (soos, byvoorbeeld, ’n mediumspanning-aandrywingstel). Om ’n beheerder met ’n hoë dinamiese optrede te ontwerp vir hoër-orde omsetterstelsels wat gemoduleer word deur OPPs is egter ’n moeilike taak en nog redelik onverken. Vir eerste-orde omsetterstelsels kan ’n nuwe industriële tegniek, wat bekend staan as modelvoorspelling-pulspatroonbeheer, ’n hoë dinamiese optrede bereik. Hierdie tesis bied ’n veralgemeende modelvoorspelling-pulspatroonbeheerder wat van toepassing is op (lineêre) hoër-orde stelsels. Deur gebruik te maak van kleinseinmodellering kan die dinamiese vergelykings van die toestandsveranderlikes van die omsetter-stelsel gelineariseer word rondom die optimale bestendigdetoestandtrajek. Dit kom as gevolg van ’n nominale bestendigdetoestandpulspatroon. ’n Belangrike aspek van die beheermetode is om die wysigings aan die pulspatroon te modelleer met die sterkte van impulse. Die gevolg is dat die wysigings aan die omsettertoestande lineêr is in die sterkte van die impulse. Die voorgestelde beheerder word geformuleer volgens die modelvoorspellingsbeheermetodologie. Danksy die lineêre interne dinamiese model kan die onderliggende optimeringsprobleem geformuleer word as ’n konveks-kwadratiese program. Volgens simulasie resultate bereik die voorgestelde beheerder ’n baie kort reaksietyd tydens oorgange en uitmuntende harmoniese optrede tydens bestendigdetoestandwerking. Die implementering van hierdie beheerstelsel op ’n lae-koste veld-programmeerbare hekskikking (FPGA) demonstreer dat die beheerder intyds kan funksioneer binne ’n kort monsterperiode van 25 µs. Tot dusver kon geen van die (min) bestaande OPP-gebasseerde beheerders vir hoër-orde stelsels daarin slaag om prakties uitvoerbaar te wees nie. Die beheermetode word verder aangepas met beperkings op die toestandsveranderlikes. Die toestandsveranderlikes word spesifiek perke gegee waarbinne hul behoort te bly. Hierdie metode word bevestig deur middel van simulasies. Die balansering van die neutrale-puntspanning word ook geïntegreer in die beheerder. Simulasies toon dat die balanseermetode goed presteer onder dinamiese toestande. Dit sluit in tydens nuldrywingsfaktor by die omsetterterminale waar die tradisionele balanseermetodes neig om te faal.af_ZA
dc.description.versionDoctoralen_ZA
dc.format.extent149 pages : illustrationsen_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/109999
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subjectSmall-signal modellingen_ZA
dc.subjectUCTDen_ZA
dc.subjectModel predictive controlen_ZA
dc.subjectOptimized pulse patternsen_ZA
dc.titleGeneralized model predictive pulse pattern control based on small-signal modellingen_ZA
dc.typeThesisen_ZA
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