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All Journal Sainstech Nusantara Maritime in Community Service and Empowerment
Muhammad Bilhaq Ashlah
Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Taiwan
Aerospace Engineering Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Physics

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Comparison of System Optimization Methods: LQR vs. LQT on the Output Response of IG-42CRGM DC Motor Muhammad Bilhaq Ashlah; Anggara Trisna Nugraha; Rama Arya Sobhita; Geniari Nastiti
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.v2i4.99

Abstract

DC motors are widely utilized in industrial applications for their reliability and efficiency. To optimize their performance, it is crucial to employ control systems supported by mathematical modeling to predict motor responses under varying conditions. This study investigates the first- and second-order models of DC motors and examines the impact of internal disturbances (noise) on system performance. The output responses of two DC motors, the 42BLFX02 and Maxon EC-I 40 (70W), are compared under both undisturbed and noisy conditions using simulations. The results reveal that the second-order model offers a more stable response and better aligns with the desired target compared to the first-order model. Furthermore, the application of the Linear Quadratic Regulator (LQR) control method significantly enhances the speed and accuracy of reaching the motor set point. However, when noise is introduced, the LQR method fails to maintain stability, and the motor's output starts to mirror the disturbance pattern. These findings highlight that while LQR is effective under ideal conditions, its performance diminishes when exposed to disturbances. Therefore, additional strategies are necessary to ensure stability and optimal performance in real-world conditions, particularly in environments with significant noise or disturbances.  
Identification and Optimization Control of a 12-Volt DC Motor System Using Linear Quadratic Regulator for Community Empowerment Muhammad Bilhaq Ashlah; Rama Arya Sobhita; Anggara Trisna Nugraha
Maritime in Community Service and Empowerment Vol. 3 No. 1 (2025): MiCSE : Maritime in Community Service and Empowerment
Publisher : Politeknik Perkapalan Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35991/micse.v3i1.332

Abstract

Direct current (DC) motors are among the most commonly utilized electric motors in various industries due to their robust and reliable regulatory characteristics. These motors also hold significant potential for application in community-based programs, particularly in renewable energy and small-scale mechanization projects that aim to empower underprivileged communities. To effectively analyze a DC motor system, it is essential to mathematically model its operational variables. This mathematical model is expressed as a transfer function, which is integrated into the simulation process using the Matlab Simulink platform. Typically, first- and second-order equations are used to represent these transfer functions. The optimization process involves the state-space representation to determine the K gain value, which is critical for achieving precise control. The Q value, derived from the multiplication of the C transpose and C matrix, directly influences the system's step response speed, while the R value is predetermined at 0.000001. Adjusting these parameters enables an optimized balance between response speed and system stability. This research provides a foundational framework for leveraging DC motor optimization in real-world applications, particularly in community empowerment programs. By enabling more efficient control mechanisms, this study contributes to the development of affordable and sustainable energy solutions, such as small-scale irrigation systems, local production facilities, or microgrid systems in remote areas.
Co-Authors Anggara Trisna Nugraha Anggara Trisna Nugraha Geniari Nastiti Rama Arya Sobhita Rama Arya Sobhita