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All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JOIV : International Journal on Informatics Visualization El-Mujtama: Jurnal Pengabdian Masyarakat
Ardilla, Fernando
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Religion Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences

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Kontrol Keseimbangan Robot Hexapod EILERO menggunakan Fuzzy Logic WIBOWO, IWAN KURNIANTO; PREISTIAN, DANY; ARDILLA, FERNANDO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 9, No 3: Published July 2021
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v9i3.533

Abstract

ABSTRAKPenelitian dengan topik robot hexapod telah banyak dikembangkan, namun sampai saat ini masih sedikit yang mengulas tentang kontrol keseimbangannya. Permasalahan yang kerap muncul adalah ketika robot berada dalam bidang miring, robot dapat terjatuh jika robot tidak dapat menyeimbangkan badan. Begitu pula dengan robot hexapod EILERO yang telah kami bangun. Untuk mengatasi permasalahan itu, selain pemodelan kinematik dan kinematika terbalik yang tepat, juga diperlukan suatu sistem keseimbangan yang baik. Dalam penelitian ini, kami menggunakan fuzzy logic untuk mengontrol keseimbangan robot EILERO dengan umpan balik data kemiringan dari sebuah sensor IMU. Setelah melalui beberapa pengujian yang komprehensif, didapatkan hasil bahwa robot dapat menyeimbangkan diri pada kondisi kemiringan papan pijakan antara -15° dan 15° pada orientasi kemiringan roll dan pitch. Robot mampu merespon dengan capaian steady state di bawah 3000 ms. Dengan demikian, robot EILERO semakin stabil dalam melintasi bidang yang tidak datar.Kata kunci: hexapod, EILERO, kinematika terbalik, fuzzy logic ABSTRACTResearch on the topic of the hexapod robot has been developed a lot, but until now there is little that has been discussed about balance control. The problem that often arises is that when the robot is on an inclined plane, the robot can fall if the robot cannot balance its body. Likewise with the EILERO hexapod robot that we have built. To solve this problem, besides proper kinematic modeling and inverse kinematic modeling, a good balance system is also needed. In this study, we used fuzzy logic to control the balance of the EILERO robot, with tilt data feedback from an IMU sensor. After going through several comprehensive tests, the results show that the robot can balance itself on the slope of the stepboards between -15 ° and 15 ° in the orientation of roll and pitch tilt. The robot is able to respond with steady state achievements below 3000 ms. Thus, the EILERO robot is increasingly stable in traversing uneven planes.Keywords: hexapod, EILERO, inverse kinematic, fuzzy logic
Penerapan Modular Smart PJU di Daerah Keputih Surabaya Bachtiar, Mochamad Mobed; Wibowo, Iwan Kurnianto; Marta, Bayu Sandi; Ardilla, Fernando
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 5 No. 1 (2025): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v5i1.6284

Abstract

  Street lighting is an important aspect of village infrastructure that affects the safety and mobility of the community. However, many villages still rely on manual systems to manage street lighting, causing inefficiencies in energy management and uncertainty in the availability of adequate lighting. The implementation of Smart PJU technology offers a solution to improve the efficiency, control, and monitoring of street lighting. However, the adoption of this technology is hampered by funding constraints and the availability of adequate devices. This study aims to develop and implement Smart PJU technology in Keputih Village, Indonesia, by involving collaboration between the Computer Engineering Study Program of PENS, village officials, and the local community. The resulting product, namely the Smart PJU Modular Device using Wireless technology, not only includes hardware for monitoring and controlling PJU lights, but also provides added value through increasing the level of domestic content (TKDN) and developing research in the Internet of Things (IoT). With this product, it has provided significant benefits to the people of Keputih Village, thus supporting and improving the quality of village infrastructure, as well as encouraging participation in the development of sustainable technology. Through this community service, the Keputih Village Community has obtained a practical solution to the problem of public street lighting and spurred innovation at the local level. Smart PJU has been installed on the PJU lights in the Keputih five-way intersection area and in front of the Keputih Village entrance. Smart PJU has been integrated with the website https://desabinaan.pens.ac.id/, where it can be monitored online whether the PJU lights are on or not, the voltage and current values ​​that flow, and allows you to control the lights remotely.
Optimizing Quadrotor Stability: RBF Neural Network Control with Performance Bound for Center of Gravity Uncertainty Yani, Mohamad; Ardilla, Fernando; Anom Besari, Adnan Rahmat; Saputra, Azhar Aulia; Kubota, Naoyuki; Ismail, Zool H
JOIV : International Journal on Informatics Visualization Vol 9, No 3 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.3.2918

Abstract

The Radial Basis Function (RBF) neural network has been widely applied for approximating nonlinear systems and improving control robustness, particularly in uncertain conditions such as dynamic shifts in the quadrotor’s Center of Gravity (COG). However, initial weight estimation errors can degrade transient responses, reducing tracking performance. This study proposes a novel RBF-based control scheme integrated with a performance-bound mechanism to enhance quadrotor stability under COG uncertainty. The performance bound ensures that the quadrotor’s motion remains within a defined region around the reference trajectory, thereby minimizing steady-state and transient errors. The RBF network is trained online to estimate the system’s dynamic changes, and the controller is designed using a Lyapunov-like function to ensure stability. Simulation results show that the proposed controller achieves better tracking accuracy and significantly lower energy usage, with total force and moment values reduced compared to the standard RBF controller. Specifically, the proposed controller uses 3010.7 N of force and 2.2427 Nm of moment, while the standard controller requires 3150.2 N and 15.197 Nm. These results confirm that the proposed method provides improved performance and energy efficiency. This research highlights the potential of integrating performance bounds in neural network control for robust quadrotor navigation. Future work includes real-world experiments to validate performance under varying COG perturbations.
Co-Authors Anom Besari, Adnan Rahmat Azhar Aulia Saputra Hasbi, Muhammad Faiz Ismail, Zool H Kubota, Naoyuki Marta, Bayu Sandi Mochamad Mobed Bachtiar, Mochamad Mobed Moh. Yani PREISTIAN, DANY Wibowo, Iwan Kurnianto