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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Darmabakti Cendekia: Journal of Community Service and Engagements Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Layanan Masyarakat (Journal of Public Service) Journal Of Sustainability Perspectives Journal of Advanced Technology and Multidiscipline (JATM) Journal of Sustainability Perspectives Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Jurnal INFOTEL Control Systems and Optimization Letters
Prisma Megantoro
Universitas Airlangga
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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Journal : Control Systems and Optimization Letters

 1 
Audio-Based Telemetry Using HT Radios for Remote Monitoring of Renewable Energy Systems Perkasa, Sigit Dani; Muzadi, Ahmad Rahmad; Megantoro, Prisma; Pandi, Vighneshwaran
Control Systems and Optimization Letters Vol 3, No 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i1.181

Abstract

Effective monitoring of renewable energy systems, such as wind turbines and photovoltaic arrays, is essential for optimizing energy production. However, traditional wired monitoring systems are expensive and lack flexibility. This study develops a reliable wireless monitoring system that addresses the limitations of wired alternatives, using a PZEM-004T power meter, Arduino Uno R3, and BF-888S HT radios. The system employs audio-modulated binary encoding for long-range, low-cost data transmission, enabling real-time monitoring of key power parameters, including voltage, current, and power factor. This solution offers scalability and cost-effectiveness by eliminating the need for extensive infrastructure. The methodology involves designing both hardware and firmware for the transmitter and receiver components and developing a communication algorithm to optimize data transfer efficiency. The system was tested in various environments: indoor, outdoor, and radio communication scenarios. Performance varied across environments, with outdoor and higher-floor tests experiencing more significant interference, which impacted transmission quality. The system achieved an average transmission time of 42.64 seconds and an error rate of 0.56% across 16 channels, demonstrating competitive reliability compared to existing wireless systems. Future research could explore adaptive modulation techniques to enhance data reliability in high-interference environments, improving the system's robustness for large-scale deployments.
Optimized Photoplethysmography-Based Classification of Calf Muscle Fatigue Using Particle Swarm Optimization with Logistic Regression Perkasa, Sigit Dani; Ama, Fadli; Megantoro, Prisma
Control Systems and Optimization Letters Vol 3, No 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i1.182

Abstract

This study investigates photoplethysmography (PPG) as a non-invasive, cost-effective alternative for real-time muscle fatigue monitoring, addressing limitations inherent to conventional methods like electromyography (EMG) and blood lactate testing. A PPG-based system was developed to classify fatigued versus non-fatigued states of the calf muscle using a DFRobot SEN0203 sensor at a 1000 Hz sampling rate. The raw PPG signals were segmented into 1-second intervals and processed to compute first and second derivatives—yielding vascular (VPG) and arterial (APG) photoplethysmograms—which enabled extraction of key features including heart rate (HR), heart rate variability (HRV), peak systolic and diastolic voltages, maximum systolic slope (u), minimum diastolic slope (v), and arterial stiffness indicators (b–a and c–a ratios). A Particle Swarm Optimization (PSO) algorithm was employed to optimize both feature selection and hyperparameters within a Logistic Regression (LR) model, achieving perfect classification accuracy (1.0) with training and prediction times of 0.0053 s and 0.0016 s, respectively. Notably, HRV and the minimum diastolic slope—reflecting autonomic regulation and vascular compliance—emerged as the most influential features with weights of 12.3747 and 23.9367. Comparative analyses revealed that although LightGBM matched the PSO-LR accuracy, neural network approaches performed poorly (0.50 accuracy), likely due to overfitting and limited training data. These findings underscore the viability of PPG for muscle fatigue monitoring, with promising applications in sports science, rehabilitation, and occupational health.
Quantum-Behaved Particle Swarm Optimization-Tuned PI Controller of a SEPIC Converter Perkasa, Sigit Dani; Megantoro, Prisma; Jasmine, Senit Araminta
Control Systems and Optimization Letters Vol 3, No 2 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i2.186

Abstract

The Single-Ended Primary Inductor Converter (SEPIC) is vital for voltage regulation in dynamic systems like renewable energy and electric vehicles. Traditional PI controllers struggle with tuning complexity and oscillations. This study introduces Quantum-Behaved Particle Swarm Optimization (QPSO) to optimize PI gains (Kp, Ki) for SEPIC converters. QPSO improves global search by using quantum-inspired probabilistic motion, overcoming issues of premature convergence seen in traditional PSO. Four objective functions—ISE, ITAE, IAE, and MSE—were evaluated to balance transient and steady-state performance. ITAE and IAE outperformed others, minimizing overshoot to 1.26% in boost mode and achieving the fastest settling time of 1,872 s. Sensitivity analysis revealed that Ki 2.0 destabilizes the system, while Kp 1.5 increases voltage ripples. The framework is computationally efficient, ideal for embedded applications. Future work should include hardware-in-loop testing to confirm robustness.
Co-Authors Abdilah, Waldi Abdillah, Muhammad Hudzaifah Abdillah, Sulthon Yusuf Abdillah, Waldi Abdufattah Yurianta Abdul Abror Abdul Latif Abror, Abdul Afif, Yusrizal Agus Mukhlisin Ahmad Rahmad Muzadi Ahmad Rahmad Muzadi Ahmad Rahmat Muzadi Aldhama, Shofa Aulia Alfian Ma’arif Ama, Fadli Ananta Sari, Feby Andino Maseleno Andrei Widjanarko Antik Widi Anugrah Anugrah, Antik Widi Apsari, Nur Fitri Arfianto, Afif Zuhri Arifin, Mohammad Aldrin Arsalan, Muhammad Rafi Nabil Arya Dwi Kustiawan Athari, Muhammad Hafizh Awalin, Lilik Jamilatul Awan Uji Krismanto Bandiyah Sri Aprillia Bilah Kebenaran Brahmantya Aji Pramudita Danar Aulia Husnan Diaz Samsun Alif Dimas Dzaky Rafii Muhammad Dimas Febriyan Priambodo Dona Saya, Joy Sefine Dwi Cahyono, Heru Effendi, Yutika Amelia Elsaved Helmy Estiko Rijanto Fadhilah, Marwan Farabi, Haikal Fatmawati Fatmawati Firdaus Bima Firmansyah Firdaus Bima Firmansyah Firdauz, Grace Constella Anastasya Gabriel De Brito Silva Galih Bangga Geston Bakti Muntoha Gunawan Setia Prihandana Hafidz Faqih Aldi Kusuma Hafizh Alauddin Atallah Hendra Ari Winarno Herlambang Setiadi Herlambang Setiadi Herri Trilaksana Heru Dwi Cahyono Heru Dwi Cahyono Hidayah, Nayu Nurrohma Hidayat, Niko Azhari Husnan, Danar Aulia I Nyoman Sutantra Ihsan Nurkhotib Indra Sidharta Irfan Helmi Sukmawan Irfan Helmi Sukmawan Irsyad Hilmi Ismayahya Ridhan Mutiarso Ismayahya Ridhan Mutiarso Iswanto Iswanto Iswanto Iswanto Jasmine, Senit Araminta Jati Galih Satrio Khadijah, Alyssa Rania Kunal Kunal Kunal, Kunal Kustanto, Bambang Joko Kustiawan, Arya Dwi Marwan Fadhilah Mian Usman Sattar Mohammad Ghani Mohammed Mareai Muda, Kemal Iskandar Muhammad Abdillah Muhammad Akbar Syahbani Muhammad Akbar Syahbani Muhammad Hudzaifah Abdillah Muhammad Rafi Nabil Arsalan Muhammad Rafi Nabil Arsalan Muhammad Syahril Mubarok Mujtahida, Fikarul Murti, Sri Muzadi, Ahmad Rahmad Nara Atthama Nayu Nurrohma Hidayah Nayu Nurrohma Hidayah Na’imah, Syahidatun Nia Maharani Raharja Nugraha, Yoga Uta Nurarsyah, Achmad Baihaqi NUrina Fitriani, NUrina Nurrohma Hidayah, Nayu Omar Tanane P. Vigneshwaran Pandi Vigneshwaran Pandi Vigneshwaran Pandi, Vighneshwaran Perkasa, Sigit Dani Phong Thanlr Nguyen Pinto Anugrah Porman Pangaribuan Pujiyanto Pujiyanto Pujiyanto Raharja, Nia Maharani Rahmania Putri Ramadhani Rania Khadijah, Alyssa Retna Apsari Rezi Delfianti Rizki Putra Prastio Rizky N. Rachman Robbi Rahim Samian Sari, Feby Ananta Sattar, Mian Usman Saud Al-Humairi, Safaa Najah Sigit Dani Perkasa Sigit Dani Perkasa Sigit Dani Perkasa Silva, Gabriel De Brito Sinta Adisti Reina Sofiah, Amila Sri Endah Nurhidayati Sri Murti Supadi Supadi Syahbani, Muhammad Akbar Syahril Mubarok, Muhammad Syamsul Arifin Syamsul Arifin Tahta Amrillah Tanane, Omar Uta Nugraha, Yoga Vigneshwaran, Pandi Widjanarko, Andrei Winarno, Hendra Ari Yoga Uta Nugraha Yoga Uta Nugraha