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Performance Analysis of Single Ended Primary Inductor Converter (SEPIC) with Adaptive and Static Proportional Integral (PI) Control Variants

Analisis Kinerja Single Ended Primary Inductor Converter (SEPIC) dengan Varian Kontrol Proporsional Integral (PI) Adaptif dan Statis

Jurnal Eksitasi · Vol. 3 No. 2 (2025)

ISSN
2829-5110
Published
2025-01-04
Publisher
Departemen Teknik Elektro
Language
id

Abstract

English

The Single-Ended Primary-Inductor Converter (SEPIC) is one type of DC-DC converter that has been widely utilized. In certain conditions, this DC-DC converter may exhibit inappropriate behavior regarding stability and reliability, thus requiring a controller to ensure that the voltage, current, or power values they produce align with the desired one. In this research, we examine and simulate the performance of the SEPIC converter using a Proportional Integral (PI) controller and compare the use of tuning methods: Ziegler-Nichols (ZN), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Fuzzy Logic in regulating the PI control parameters. Simulations will be performed through MATLAB. From the simulation results, it is observed that the PI tuning methods using GA, PSO, and Fuzzy Logic are superior to the ZN method, and with the advantage of adaptive process for PI tuning, the fuzzy logic method outperforms in terms of convenience to the other three methods.

Bahasa Indonesia

Single-Ended Primary-Inductor Converter (SEPIC) merupakan salah satu jenis konverter DC-DC yang telah banyak digunakan. Pada kondisi tertentu, konverter DC-DC ini dapat menunjukkan perilaku yang tidak sesuai terkait stabilitas dan keandalan, sehingga memerlukan pengontrol untuk memastikan bahwa nilai tegangan, arus, atau daya yang dihasilkannya sesuai dengan yang diinginkan. Dalam penelitian ini, kami menguji dan mensimulasikan kinerja konverter SEPIC menggunakan pengontrol Proportional Integral (PI) dan membandingkan penggunaan metode penyetelan: Ziegler-Nichols (ZN), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), dan Fuzzy Logic dalam mengatur parameter kontrol PI. Simulasi akan dilakukan melalui MATLAB. Dari hasil simulasi, dapat diamati bahwa metode penyetelan PI menggunakan GA, PSO, dan Fuzzy Logic lebih unggul daripada metode ZN, dan dengan keunggulan proses adaptif untuk penyetelan PI, metode logika fuzzy mengungguli dalam hal kenyamanan dibandingkan dengan tiga metode lainnya.

Keywords

Collaboration network of the authors

9 authors · 12 co-authorship links

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Co-authorOrganisationJoint articles
Ilham RamliAffiliation unknown1
Sri Mawar SaidAffiliation unknown1
Muh AnsharAffiliation unknown1
Zulkifli ArfahAffiliation unknown1
Gabriel Jeremia MardolinaAffiliation unknown1
A. Ejah Umraeni SalamAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/eksitasi/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Performance Analysis of Single Ended Primary Inductor Converter (SEPIC) with Adaptive and Static Proportional Integral  (PI) Control Variants</dc:title>
	<dc:title xml:lang="id">Analisis Kinerja Single Ended Primary Inductor Converter (SEPIC) dengan Varian Kontrol Proporsional Integral (PI) Adaptif dan Statis</dc:title>
	<dc:creator xml:lang="en">A. Nur Annisa Alif Panawan</dc:creator>
	<dc:creator xml:lang="en">Faizal Arya Samman</dc:creator>
	<dc:creator xml:lang="en">Ida Rachmaniar Sahali</dc:creator>
	<dc:creator xml:lang="id">A. Nur Annisa Alif Panawan</dc:creator>
	<dc:creator xml:lang="id">Faizal Arya Samman</dc:creator>
	<dc:creator xml:lang="id">Ida Rachmaniar Sahali</dc:creator>
	<dc:subject xml:lang="en">SEPIC (Single-Ended Primary-Inductor Converter)</dc:subject>
	<dc:subject xml:lang="en">PI (Proportional Integral)</dc:subject>
	<dc:subject xml:lang="en">GA (Genetic Algorithm)</dc:subject>
	<dc:subject xml:lang="en">PSO (Particle Swarm Optimization)</dc:subject>
	<dc:subject xml:lang="en">Fuzzy Logic</dc:subject>
	<dc:subject xml:lang="id">SEPIC (Single-Ended Primary-Inductor Converter)</dc:subject>
	<dc:subject xml:lang="id">PI (Proportional Integral)</dc:subject>
	<dc:subject xml:lang="id">GA (Genetic Algorithm)</dc:subject>
	<dc:subject xml:lang="id">PSO (Particle Swarm Optimization)</dc:subject>
	<dc:subject xml:lang="id">Fuzzy Logic</dc:subject>
	<dc:description xml:lang="en">The Single-Ended Primary-Inductor Converter (SEPIC) is one type of DC-DC converter that has been widely utilized. In certain conditions, this DC-DC converter may exhibit inappropriate behavior regarding stability and reliability, thus requiring a controller to ensure that the voltage, current, or power values they produce align with the desired one. In this research, we examine and simulate the performance of the SEPIC converter using a Proportional Integral (PI) controller and compare the use of tuning methods: Ziegler-Nichols (ZN), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Fuzzy Logic in regulating the PI control parameters. Simulations will be performed through MATLAB. From the simulation results, it is observed that the PI tuning methods using GA, PSO, and Fuzzy Logic are superior to the ZN method, and with the advantage of adaptive process for PI tuning, the fuzzy logic method outperforms in terms of convenience to the other three methods.</dc:description>
	<dc:description xml:lang="id">Single-Ended Primary-Inductor Converter (SEPIC) merupakan salah satu jenis konverter DC-DC yang telah banyak digunakan. Pada kondisi tertentu, konverter DC-DC ini dapat menunjukkan perilaku yang tidak sesuai terkait stabilitas dan keandalan, sehingga memerlukan pengontrol untuk memastikan bahwa nilai tegangan, arus, atau daya yang dihasilkannya sesuai dengan yang diinginkan. Dalam penelitian ini, kami menguji dan mensimulasikan kinerja konverter SEPIC menggunakan pengontrol Proportional Integral (PI) dan membandingkan penggunaan metode penyetelan: Ziegler-Nichols (ZN), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), dan Fuzzy Logic dalam mengatur parameter kontrol PI. Simulasi akan dilakukan melalui MATLAB. Dari hasil simulasi, dapat diamati bahwa metode penyetelan PI menggunakan GA, PSO, dan Fuzzy Logic lebih unggul daripada metode ZN, dan dengan keunggulan proses adaptif untuk penyetelan PI, metode logika fuzzy mengungguli dalam hal kenyamanan dibandingkan dengan tiga metode lainnya.</dc:description>
	<dc:publisher xml:lang="id">Departemen Teknik Elektro</dc:publisher>
	<dc:date>2025-01-04</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="id">Artikel Peer-review</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/eksitasi/article/view/42795</dc:identifier>
	<dc:source xml:lang="en">Jurnal Eksitasi; Vol. 3 No. 2 (2024): Jurnal Eksitasi Departemen Teknik Elektro. Vol. 3. No. 2. 2024</dc:source>
	<dc:source xml:lang="id">JURNAL EKSITASI DEPARTEMEN TEKNIK ELEKTRO; Vol 3 No 2 (2024): Jurnal Eksitasi Departemen Teknik Elektro. Vol. 3. No. 2. 2024</dc:source>
	<dc:source>2829-5110</dc:source>
	<dc:language>id</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/eksitasi/article/view/42795/12416</dc:relation>
</oai_dc:dc>