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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Indonesian Journal of Electrical Engineering and Computer Science Journal of Advanced Technology and Multidiscipline (JATM)
Herlambang Setiadi
Universitas Airlangga
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Journal : International Journal of Electrical and Computer Engineering

 1 
All-terrain mobile robot desinfectant sprayer to decrease the spread of COVID-19 in open area Prisma Megantoro; Herlambang Setiadi; Brahmantya Aji Pramudita
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2090-2100

Abstract

The application of disinfection is becoming popular in recent months due to the COVID-19. Usually, the disinfection is used by spraying the liquid into an object. However, the disinfection process for humans and objects in the human environment is still done manually and takes time and increases exposure to viruses. Robotic technology can be a solution to handle that problem. Following that problem, robot design is proposed with many abilities and features. The robot can operate in remote conditions and full function for approximately 56 minutes and spray the liquid for more than 1 meter. This research can effectively be applied in COVID-19 handlings.
Adaptive virtual inertia controller based on machine learning for superconducting magnetic energy storage for dynamic response enhanced Herlambang Setiadi; Muhammad Abdillah; Yusrizal Afif; Rezi Delfianti
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp3651-3659

Abstract

The goal of this paper was to create an adaptive virtual inertia controller (VIC) for superconducting magnetic energy storage (SMES). An adaptive virtual inertia controller is designed using an extreme learning machine (ELM). The test system is a 25-bus interconnected Java Indonesian power grid. Time domain simulation is used to evaluate the effectiveness of the proposed controller method. To simulate the case study, the MATLAB/Simulink environment is used. According to the simulation results, an extreme learning machine can be used to make the virtual inertia controller adaptable to system variation. It has also been discovered that designing virtual inertia based on an extreme learning machine not only makes the VIC adaptive to any change in the system but also provides better dynamics performance when compared to other scenarios (the overshoot value of adaptive VIC is less than -5×10-5).
Co-Authors Afif, Yusrizal Akbar Swandaru Awan Uji Krismanto Brahmantya Aji Pramudita Danang Sulistyo Fakhruddin Arrazi Firdaus Bima Firmansyah Galih Bangga Herri Trilaksana Muhammad Abdillah Muhammad Aldo Setiawan Prisma Megantoro Rezi Delfianti Rizki Putra Prastio Rodik Wahyu Indrawan Tahta Amrillah Teguh Aryo Nugroho