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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Teknosains Journal of Environment and Sustainability Jurnal Elektronika dan Telekomunikasi JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Celebes Education Review Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Engineering and Technology (INAJET) INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Jurnal Teknik Elektro (JTE) Jurnal Pendidikan Teknik Elektro ELPOSYS: Jurnal Sistem Kelistrikan Journal of Electrical Engineering Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Widi Aribowo
Universitas Negeri Surabaya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Transportation Other

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Journal : Journal of Robotics and Control (JRC)

 1 
A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer Aribowo, Widi
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.16445

Abstract

Power system stabilizer (PSS) is applied to dampen system oscillations so that the frequency does not deviate beyond tolerance. PSS parameter tuning is increasingly difficult when dealing with complex and nonlinear systems. This paper presents a novel hybrid algorithm developed from incorporating chaotic maps into the sea-horse optimizer. The algorithm developed is called the chaotic sea-horse optimizer (CSHO). The proposed method is adopted from the metaheuristic method, namely the sea-horse optimizer (SHO). The SHO is a method that duplicates the life of a sea-horse in the ocean when it moves, looks for prey and breeds.  In This paper, The CSHO method is used to tune the power system stabilizer parameters on a single machine system. The proposed method validates the benchmark function and performance on a single machine system against transient response. Several metaheuristic methods are used as a comparison to determine the effectiveness and efficiency of the proposed method. From the research, it was found that the application of the logistics Tent map from the chaotic map showed optimal performance. In addition, the application of the PSS shows effective and efficient performance in reducing overshoot in transient conditions.
A Novel Hybrid Prairie Dog Optimization Algorithm - Marine Predator Algorithm for Tuning Parameters Power System Stabilizer Aribowo, Widi; Rohman, Miftahur; Baskoro, Farid; Harimurti, Rina; Yamasari, Yuni; Yustanti, Wiyli
Journal of Robotics and Control (JRC) Vol 4, No 5 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i5.19521

Abstract

The article presents the parameter tuning of the Power System Stabilizer (PSS) using the hybrid method. The hybrid methods proposed in this article are Praire Dog Optimization (PDO) and Marine Predator Algorithm (MPA). The proposed method can be called PDOMPA. In the PDOMPA method, the marine predator algorithm (MPA) is able to search around optimal individuals when updating population positions. MPA is used to make the exploration and exploitation stages of PDO more valid and accurate. PDO is an algorithm inspired by the life of prairie dogs. Prairie dogs are adapted to colonizing in burrows underground. Prairie dogs have daily habits of eating, observing for predators, establishing fresh burrows, or preserving existing ones. Meanwhile, MPA is a duplication of marine predator life which is modeled mathematically. In order to validate the performance of the PDOMPA method, this article presents a comparative simulation of the objective function and the transient response of PSS. This research uses validation by comparing with conventional methods, Whale Optimization Algorithm (WOA), Grasshopper Optimization Algorithm (GOA), Marine Predator Algorithm (MPA), and Praire Dog Optimization (PDO). Based on the simulation results, PDOMPA presents fast convergence in some cases and shows optimal results compared to competitive algorithms. From the simulation results using load variations, it was found that the proposed method has the ability to reduce the average undershoot and overshoot of speed by 42.2% and 85.37% compared to the PSS-Lead Lag method. Meanwhile the average settling time value of speed is 50.7%.
Improved Droop Control Based on Modified Osprey Optimization Algorithm in DC Microgrid Aribowo, Widi; Suryoatmojo, Heri; Pamuji, Feby Agung
Journal of Robotics and Control (JRC) Vol 5, No 3 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i3.21347

Abstract

In this research, a modified Osprey optimization algorithm (MOOA) is presented to optimize droop control parameters. MOOA is a modification of the Osprey optimization algorithm by adding levy flight which has the advantage of exploiting a wider space and being adaptive to environmental changes. This research also modifies droop control, Proportional Integral Derivative (PID) is applied to secondary control. PID has flexibility in responding to changes in system conditions and fast response in dealing with system changes. The PID parameters are optimized using MOOA and are called MOOA-PID. The MOOA method is validated using 23 CEC2017 benchmarks-function and performance on DC microgrid systems. This research uses the latest algorithms as a comparison, namely One-to-One Based Optimizer (OOBO), Preschool Educational Optimization Algorithm (PEOA), and the red-tailed hawk (RTH) algorithm in testing 23 CEC2017 benchmark functions. From the simulation of the 23 CEC2017 benchmark function, it is known that the MOOA method has better capabilities. MOOA has advantages in 15 out of 23 benchmark functions. In DC microgrid system testing, MOOA-PID is compared with the Proportional Integral (PI) method which is optimized with MOOA and is called MOOA-PI. Testing on the microgrid is aimed at determining the performance of the transient response of power, voltage and current in the system. Tests on DC microgrid systems found that the application of MOOA-PID in secondary control had better capabilities than MOOA-PI. The average value of voltage overshoot from MOOA-PID is 9.828% better than MOOA-PI. The average ITSE MOOA-PID score is 22.3% better than MOOA-PI.
Monitoring DC Motor Based On LoRa and IOT Suhermanto, Dimas Ahmad Nur Kholis; Aribowo, Widi; Shehadeh, Hisham A.; Rahmadian, Reza; Widyartono, Mahendra; Wardani, Ayusta Lukita; Hermawan, Aditya Chandra
Journal of Robotics and Control (JRC) Vol 5, No 1 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i1.19642

Abstract

Electrical energy efficiency is a dynamic in itself that continues to be driven by electrical energy providers. In this work, long-range (LoRa) technology is used to monitor DC motors. In the modern world, IoT is becoming increasingly prevalent. Embedded systems are now widely used in daily life. More can be done remotely in terms of control and monitoring. LoRa is a new technology discovered and developing rapidly. LoRa technology addresses the need for battery-operated embedded devices. LoRa technology is a long-range, low-power technology. In this investigation, a LoRa transmitter and a LoRa receiver were employed. This study employed a range of cases to test the LoRa device. In the first instance, there are no barriers, whereas there are in the second instance. The results of the two trials showed that the LoRa transmitter and receiver had successful communication. In this study, the room temperature is used to control DC motors. So that the DC motor's speed adjusts to fluctuations in the room's temperature. Additionally, measuring tools and the sensors utilised in this investigation were contrasted. The encoder sensor and the INA 219 sensor were the two measured sensors employed in this study. According to the findings of the experiment, the tool was functioning properly.
A Comparative Study of Metaheuristic Optimization Algorithms in Solving Engineering Designing Problems Aribowo, Widi; Shehadeh, Hisham A.
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.26410

Abstract

This paper presents a comprehensive comparative study of several metaheuristic optimization algorithms with the aim of identifying the most effective method for solving well-established engineering design problems. The algorithms selected for this study include Sperm Swarm Optimization (SSO), Chernobyl Disaster Optimizer (CDO), Bermuda Triangle Optimizer (BTO), Marine Predators Algorithm (MPA), and Particle Swarm Optimization (PSO). These algorithms are tested and evaluated through both qualitative and quantitative analyses.The first phase of testing involves applying the algorithms to a set of benchmark functions from the Congress on Evolutionary Computation (CEC) 2017 suite. Key performance indicators such as best fitness value, standard deviation, and mean are used to measure solution quality, while convergence curves are analyzed to assess optimization efficiency over iterations. This allows for a robust evaluation of each algorithm's ability to balance exploration and exploitation in the search space. In the second phase, the algorithms are implemented to solve real-world engineering design problems, including Speed Reducer Design, Pressure Vessel Design, Cantilever Beam Design, and Robot Gripper Optimization. These case studies further validate the practical applicability and versatility of the algorithms in handling complex, multidimensional, and constrained optimization tasks. The results indicate varying levels of performance across different problems, highlighting the strengths and limitations of each method. This comparative insight provides valuable guidance for researchers and practitioners in selecting suitable optimization techniques for specific engineering challenges.
Co-Authors A. Shehadeh, Hisham A.A. Ketut Agung Cahyawan W Abualigah, Laith Achmad Imam Agung ACHMAD RIZAL MAWALI Achmad, Fendi Ade Ananda Kurniawan Adhim Triano Nasrullah Aditya Chandra Hermawan Aditya Chandra Hermawan Aditya Prapanca Agus Budi Santosa Agus Budi Santosa Agustin, Intan Permata Ainul, Safira Tri Handini Akhmad Rizqi Kamal Aljohani, Abeer Amaliah, Fithrotul Irda Andi Iwan Nurhidayat Arief, Muhammad Baharuddin Arief, Rozihan Ariyanto, Sudirman Rizki Arrashid, Rakhmad Arrashid, Rakhmad Agus Asmunin Asmunin As’ad Shidqy Aziz Ayusta Lukita Wardani B, Nur Vidia Laksmi B., I Gusti Putu Asto Bambang Suprianto . Bao, Benesiktus Chandra Hermawan, Aditya Danang Aji Basudewa Dimas Herjuno Dwi, Mochamad Hanif Edy Kurniawan Effendi, Moh. Zaenal Elsayed Abd Elaziz, Mohamed Erfin Prafitama Setiawan , Muhammad Erina Rahmadyanti Euis Ismayati Farid Baskoro Faruqi, Muhammad Ismail Feby Agung Pamuji Fendi Achmad Firdaus, Muhammad Riqi Fransisca, Yulia Hacimahmud Abdullayev, Vugar Hafid Al azzah Heri Suryoatmojo Hermawan , Aditya Chandra Hermawan,, Aditya Chandra Herwanto , Yoko Ibrohim Ibrohim Ibrohim Igo Nanda Deka Zaymapa Ilham Amarulloh Ismet Basuki Joko Joko Kevin Pranata Putra Khoirul Anwar Khoriri, Doddy Nur Liu, Tian-Hua Lucia Tri Pangesthi Lukita Wardani , Ayusta Luthfiyah Nurlela Ma'arif, Muhammad Fikrul Mahendra Widyartono Mochamad Hanif Dwi Wicaksono Mubarok, Muhammad Syahril MUHAMMAD PERMANA SETYA GUNAWAN Muhammad Syahril Mubarok Muhammad Taufiqurrohman, Muhammad Munoto Munoto Musthofa, Achmad Malikur Robbani Mzili, Toufik Nawawi , Akhmad Nita Kusumawati Nugrahani Astuti Nugroho, Yuli Sutoto Nur Vidia Laksmi B Nurlita, Ita Nurul Jaizah Oliva , Diego Oliva, Diego Pradipta, Moh. Alfiansyah Putera Putra, Alfredo Arianto Permana Putra, Andreas Perkasa Raden Mohamad Herdian Bhakti Rahmadian, Reza Rakhmad Agus Arrashid Ridwan, M. Nanda Tri Maulana Rina Harimurti Rosalin, Berliana Dzakiyya Ruzairi Abdul rahim Sabo, Aliyu Salam, Muhammad Abdus Shehadeh, Hisham A. Siti Sulandjari Soleimanian Gharehchopogh, Farhad Sri . Handayani Subuh Isnur Haryudo Suhermanto, Dimas Ahmad Nur Kholis Supari Muslim Supari Supari Syamsul Muarif Taufiqur Rohman Udin, Muhammad Syafi Umaroh, Susi Tri Unit Three Kartini Wicaksono, Alfiyanto Wahyu Wicaksono, Mochamad Hanif Dwi Widiyartono, Mahendra Wiyli Yustanti WRAHATNOLO, TRI YUNI YAMASARI Zahrotul Maulia Zangana, Hewa Majeed Zaymapa, Igo Nanda Deka