Utilization of Linear Quadratic Regulator (LQR) and Linear Quadratic Tracker (LQT) Models for Improving Energy Efficiency in RS 224-8636 DC Motors in the Context of Community Service - Hulyan Denny Afriyansah (Politeknik Perkapalan Negeri Surabaya, 2024)
Optimal control systems have gained significant attention in recent years due to the growing demand for high-performance systems. The optimization concept in control systems balances the selection of performance indices and engineering constraints to achieve an optimal control system within physical limitations. In addressing optimal control systems, it is essential to determine a control rule that minimizes the deviation from ideal system behavior. This study focuses on the application of Linear Quadratic Regulator (LQR) and Linear Quadratic Tracker (LQT) models to improve energy efficiency in DC motors, specifically the RS 224-8636 model, as a solution for community service in maritime settings. The research begins by identifying the DC motor's parameters through datasheet analysis and simulating the control model using MATLAB software. After obtaining the necessary datasheet information, first-order mathematical modeling is conducted. The next step involves testing the LQR and LQT circuits in MATLAB, followed by analyzing the results and drawing conclusions. Additionally, the experiments include comparing first-order Simulink simulations with simulations of LQR under two conditions: without noise and with noise interference. The findings indicate that the addition of noise introduces significant deviations in the system's response. Noise interference degrades the quality of the received signal, leading to disruptions in data transmission and processing. These results are particularly relevant in designing robust control systems for real-world applications in energy optimization for maritime communities. By addressing challenges such as noise interference, this research contributes to the development of resilient and efficient energy systems, which can be implemented to enhance the sustainability and economic independence of communities.