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Efficiency Of Generator Set On Changes In Electrical Load On Fishery Vessels Fahmi Yahya Saputra; Rama Arya Sobhita; Anggara Trisna Nugraha; Akhmad Azhar Firdaus
MEIN : Journal of Mechanical, Electrical & Industrial Technology Vol. 1 No. 2 (2024): MEIN : Journal of Mechanical, Electrical & Industrial Technology
Publisher : P3M Politeknik Perkapalan Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35991/mein.v1i2.2

Abstract

Electrical energy is an essential requirement for fishing vessels, and it is primarily generated by diesel-driven electric generators. This energy is utilized for various purposes onboard such as lighting, navigation, and supporting fishing activities including loading and unloading. The efficient operation and longevity of the electric generator onboard depend on ensuring that the load imposed on it does not surpass its capacity. Researchers conducted several phases in this study, including identifying the electrical power distribution system, determining the generator capacity and the electrical load it receives, and calculating the electrical load under various operational conditions. Additionally, the study examined the operational efficiency of the generator under four different conditions. The findings reveal that the fishing vessel employs a radial electrical distribution system and is equipped with two electric generators, each having a capacity of 225 kVA. The generators demonstrate efficient performance across all operational scenarios, with load factors ranging from 79.70% to 83.08%.
System Optimization Using LQR and LQT Methods on 42D29Y401 DC Motor Nugraha, Anggara Trisna; Akhmad Azhar Firdaus; Rama Arya Sobhita; Zaki Wicaksono
SAINSTECH NUSANTARA Vol. 2 No. 2 (2025): May 2025
Publisher : Nusantara Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71225/jstn.v2i2.108

Abstract

Control systems are critical for managing, commanding, and regulating the behavior of dynamic systems. A DC motor converts direct current electrical energy into kinetic energy, requiring positive and negative voltage terminals for operation. Due to their ease of control across wide speed ranges, DC motors are widely applied in various industrial sectors. Speed regulation is typically achieved using control devices tailored to specific system requirements. To optimize DC motor performance, this study employs mathematical modeling and control strategies using MATLAB software. The 42D29Y401 DC motor is modeled and simulated using the Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) methods. Simulation results show that the first-order DC motor achieved a stable step response with an amplitude of 3.40, a rise time of 3.11 seconds, and minor overshoot and undershoot values of 0.501% and 1.98%, respectively. The LQR-optimized system improved performance with an amplitude close to 1, a faster rise time of 1.1 seconds, and reduced overshoot and undershoot at 0.505%. Comparatively, the LQR-based system demonstrated better overall performance than the unoptimized model, while the LQT-based system yielded the highest level of performance among all configurations.
Enhancing LQR and LQT Control Strategies for the Output Performance of PG36M555 DC Motors Akhmad Azhar Firdaus; Nugraha, Anggara Trisna; Rama Arya Sobhita; Dhadys Ayu Juli Anjhani
SAINSTECH NUSANTARA Vol. 2 No. 4 (2025): November 2025
Publisher : Nusantara Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71225/jstn.v2i4.101

Abstract

A DC motor is commonly utilized as an actuator due to its ability to produce high torque. Controlling the motor's speed is one of the primary methods to manage its performance. Among various wireless communication options, radio waves are preferred since they do not require a clear line of sight between the transmitter and receiver. Employing multiple antennas offers benefits such as enhanced reliability and increased data transmission rates. This study focuses on designing and simulating four types of systems: SISO, SIMO, MISO, and MIMO. The performance of these configurations is evaluated and compared using Signal-to-Noise Ratio (SNR) and channel capacity, with variations in antenna count. Simulations were carried out in MATLAB to analyze how different antenna quantities (4, 8, and 16) affect channel capacity across an SNR range of 0 to 30 dB. The simulation outcomes reveal a substantial rise in system capacity, reaching up to 214 bits/Hz/sec when a 16x16 MIMO setup is applied at 30 dB SNR.