System Identification Based Fractional Order Plant Realization on an FPGA

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dc.contributor.authorPektas, Omer
dc.contributor.authorCelik, Orkan Murat
dc.contributor.authorKoseoglu, Murat
dc.date.accessioned2026-04-04T13:19:00Z
dc.date.available2026-04-04T13:19:00Z
dc.date.issued2025
dc.departmentİnönü Üniversitesi
dc.description9th International Artificial Intelligence and Data Processing Symposium, IDAP 2025 -- 6 September 2025 through 7 September 2025 -- Malatya -- 215321
dc.description.abstractThe control of actuators for diverse applications is gaining increasing importance across both industrial domains and everyday technologies. Classical control algorithms are progressively being replaced by more advanced and intelligent control methodologies, in parallel with advancements in computational power, particularly in CPUs, GPUs, FPGAs and even MCUs. Traditional approaches, such as Proportional-Integral-Derivative (PID) and Proportional-Integral (PI) controllers, are giving way to data-driven control techniques. These modern methods typically rely on an accurate mathematical model of the plant. Consequently, the fidelity of this model in representing the real system plays a crucial role in the overall performance and reliability of data-driven control strategies. In this study, a fractional-order (FO) system identification process was applied to a real DC motor-driver system to develop a more accurate dynamic model. The identified FO model was validated through various methods to ensure its fidelity to the actual system. To enable efficient implementation, the FO model was approximated by an equivalent integer-order model and subsequently reduced to lower its computational complexity. To evaluate its suitability for embedded control applications, the reduced model was implemented and simulated on an FPGA platform. Comprehensive simulation and experimental analyses, including frequency and step response evaluations, were performed to assess the performance and practicality of the FPGA-based implementation. The results highlight the potential of the proposed approach for real-time control and signal processing applications. © 2025 IEEE.
dc.identifier.doi10.1109/IDAP68205.2025.11222383
dc.identifier.isbn979-833158990-5
dc.identifier.scopus2-s2.0-105024999599
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/IDAP68205.2025.11222383
dc.identifier.urihttps://hdl.handle.net/11616/108075
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof9th International Artificial Intelligence and Data Processing Symposium, IDAP 2025
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250329
dc.subjectFPGA
dc.subjectFractional Modelling and Control
dc.subjectSystem Identification
dc.subjectSystem Modelling
dc.titleSystem Identification Based Fractional Order Plant Realization on an FPGA
dc.typeConference Object

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