Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Mechatronics, Electrical Power, and Vehicular Technology RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Arya Kusumawardana
State University of Malang
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Adaptive frequency regulation of an LPG generator using an assistive model-free iterative learning controller Inov Ivandany; Arya Kusumawardana; Muhammad Afnan Habibi; Muhammad As'ad Sahroni
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1372

Abstract

Mechanical speed governors in small generator sets often provide only coarse frequency regulation, leading to steady-state error and poor transient recovery under load disturbances. To address this limitation, this study proposes a hybrid governor for an (liquefied petroleum gas) LPG-converted generator, in which the built-in mechanical governor is retained as the primary stabilizing layer, and a model-free iterative learning control (ILC) is added as an assistive electronic controller. The proposed method was validated experimentally under dynamic multi-step load disturbances and internal parameter shifts. In the dynamic load test, the proposed hybrid ILC achieved the lowest root mean square error (RMSE) of 0.9144 Hz, compared with 0.9581 Hz for the (proportional-integral) PI-controller benchmark and 1.5512 Hz for the mechanical governor. This corresponds to an RMSE improvement of 41.05 % relative to the mechanical governor and 4.56 % relative to the PI-controller benchmark. In terms of relative tracking accuracy, both electronic controllers substantially reduced the mean absolute percentage error (MAPE) relative to the mechanical governor, with the proposed hybrid ILC achieving the lowest value of 1.14 %, slightly lower than 1.15 % for the PI-controller and much lower than 2.04 % for the mechanical governor. Under internal parameter detuning, the proposed method maintained better regulation performance, with RMSE improvements reaching 79.68 % relative to the mechanical baseline. These results show that the proposed hybrid model-free ILC improves transient response, tracking accuracy, and robustness, while preserving the original mechanical governor as a practical baseline controller.
IMPLEMENTASI SISTEM MONITORING DAN KENDALI GENSET LPG SECARA NEAR REAL-TIME MENGGUNAKAN ESP32-S3 DAN FIREBASE: IMPLEMENTATION OF A NEAR REAL-TIME LPG GENERATOR MONITORING AND CONTROL SYSTEM USING ESP32-S3 AND FIREBASE Muhammad Arzu Prasetyo; Arya Kusumawardana; Soraya Norma Mustika; Royb Fatkhur Rizal
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7135

Abstract

Manual monitoring of generators often leads to delays in detecting malfunctions and is unable to provide near real-time data. This study aims to design and implement an Internet of Things (IoT)-based monitoring and control system for LPG generators using an ESP32-S3 microcontroller integrated with Firebase and an Android application called GENMON (Genset Monitoring System). The system is designed to measure various operational parameters of the generator, including voltage, current, power, temperature, and gas pressure, and to transmit these data continuously to Firebase for display through the Android application. In addition to presenting parameter information, the system is equipped with an automatic notification feature that triggers when abnormal conditions are detected, as well as remote-control functionality for starting and shutting down the generator. This research adopts a practice-based methodology encompassing the design of both hardware and software, followed by system performance testing and application functionality evaluation. Based on the test results, the system demonstrated good performance, with voltage sensor accuracy reaching 98.5%, frequency sensor accuracy reaching 99.33%, and current sensor accuracy reaching 100%, an average notification delay of 1.76 seconds, data transmission latency ±1 second, data synchronization success rate of 90%, and a control response time ranging from 1 to 2 seconds.
Co-Authors Inov Ivandany Muhammad Afnan Habibi Muhammad Arzu Prasetyo Muhammad As'ad Sahroni Royb Fatkhur Rizal Soraya Norma Mustika