Lyapunov-based model predictive control of dual-induction motors fed by a nine-switch inverter to improve the closed-loop stability

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dc.authoridKomurcugil, Hasan/0000-0003-4728-6416
dc.contributor.authorGulbudak, Ozan
dc.contributor.authorGokdag, Mustafa
dc.contributor.authorKomurcugil, Hasan
dc.date.accessioned2024-09-29T15:57:15Z
dc.date.available2024-09-29T15:57:15Z
dc.date.issued2023
dc.departmentKarabük Üniversitesien_US
dc.description.abstractThis study presents a novel Lyapunov-based model predictive control strategy for a nine-switch inverter-based multi-drive system. The drive system includes two ac motors and a single nine-switch inverter (NSI) that is capable of feeding the multiple induction motors. The model predictive control (MPC) is a popular feedback strategy in ac-drive applications due to its fast dynamic characteristics and the skill of handling multiple control goals. Although the MPC offers a rapid dynamic response to load variations, it suffers from closed-loop instability when the cost function is poorly designed. The unwise choice of the tuning parameters, cost function terms, and control constraints cause instability resulting in poor system performance. In particular, the formulation of the selected objective function greatly impacts the closed-loop stability since it tailors the closed-loop characteristics. A simple penalization of the control goal error in the cost function may not ensure asymptotic stability. Motivated by the MPC stability problem, the cost function is reformulated as a Lyapunov energy function to strengthen the closed-loop stability in this paper. The proposed method selects the control input that meets the Lyapunov stability criterion and applies it to the multi-motor driver. The proposed strategy ensures asymptotic stability and provides a robust motor operation by introducing the Lyapunov control constraints. The proposed feedback strategy is experimentally verified using a lab-scaled hardware test platform. The experimental results demonstrate that the suggested control routine offers an improved steady-state characteristic compared to the conventional MPC method. (c) 2017 Elsevier Inc. All rights reserved.en_US
dc.identifier.doi10.1016/j.ijepes.2022.108718
dc.identifier.issn0142-0615
dc.identifier.issn1879-3517
dc.identifier.scopus2-s2.0-85140903359en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.ijepes.2022.108718
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4708
dc.identifier.volume146en_US
dc.identifier.wosWOS:000881608700004en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofInternational Journal of Electrical Power & Energy Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNine -switch inverteren_US
dc.subjectModel predictive controlen_US
dc.subjectReceding -horizon controlen_US
dc.subjectLaypunov stabilityen_US
dc.subjectMulti -drive systemen_US
dc.titleLyapunov-based model predictive control of dual-induction motors fed by a nine-switch inverter to improve the closed-loop stabilityen_US
dc.typeArticleen_US

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