LQR and LQT System Optimization Models to Improve the Output Response Performance of Brushless DC Motors (BLDC) in the Context of Maritime Community Empowerment

Ilham Akbar Syafa'atullah (Marine Electrical Engineering Study Program, Department of marine Electrical Engineering, Shipbuilding Institute of Polytechnic Surabaya, Jl. Chemical Engineering, ITS Sukolilo Campus, Surabaya 6011, Indonesia.)

Maritime in Community Service and Empowerment
Vol. 1 No. 1 (2023): MiCSE : Maritime in Community Service and Empowerment

Brushless DC Motors (BLDC) are essential components commonly found in industrial settings and daily applications. To ensure optimal performance, control systems are required to enhance the operational efficiency of these motors. Modeling plays a critical role in determining whether the inherent response of a BLDC motor, even before applying a load, meets the desired performance criteria. Common plant models include SISO, SIMO, MISO, and MIMO systems, each requiring a mathematical representation to illustrate system responses through graphical outputs generated using software tools. This research focuses on the mathematical modeling of first-order and second-order BLDC motors, specifically the 42BLFX02 type, and examines their responses under different configurations, both with and without noise. In real-world scenarios, it is unrealistic for a plant to operate without disturbances, with internal noise being a common issue that impacts system performance. The study aims to compare the responses of first-order and second-order BLDC motors modeled in SISO, SIMO, MISO, and MIMO configurations, highlighting the effects of noise disturbances. Results indicate that the SISO model without noise exhibits the most optimal response, characterized by linear behavior and the absence of ripples. Additionally, second-order mathematical models produce responses closer to the setpoint values compared to first-order models. In MISO and MIMO configurations, the system's output responses tend to align with the shape of one of the input signals. Furthermore, noise inclusion causes the motor's output response to mimic the shape of the introduced noise signals. This study contributes to the development of control systems by providing insights into motor response behavior under various modeling configurations. The findings have significant implications for empowering maritime communities, particularly by optimizing energy-efficient BLDC motor applications in vessels to improve operational reliability and reduce energy consumption.