The rapid advancement of telecommunications has significantly influenced various engineering applications, including control systems for electrical and mechanical systems. One crucial aspect of control system design is ensuring signal integrity and stability, particularly in Single-Input Single-Output (SISO) circuits. In this study, we analyze the performance of a DC motor within a SISO circuit using Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) control methods. The research employs a simulation-based approach, evaluating first-order and second-order system responses under different conditions, including scenarios with and without external noise interference. Experimen... More >

Optimization is a critical approach in decision-making processes aimed at enhancing both safety and operational efficiency in industrial systems. This research focuses on the implementation of the Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) control strategies to optimize the FL57BL02 DC motor control system, widely used in industrial automation, particularly in high-risk applications such as conveyors and robotic systems. The LQR method is employed to enhance system stability by minimizing output deviations and ensuring optimal control performance under varying load conditions. Meanwhile, LQT is utilized to improve trajectory tracking accuracy, ensuring that the syst... More >

Accurately determining the state of charge (SOC) is a critical factor in effective energy management for electric vehicles (EVs). Therefore, SOC variations in battery packs must be assessed with high precision. To simulate the complex processes within EVs that involve lithium-ion batteries (LIBs), an appropriate battery model is essential. Accurate parameter extraction through algorithmic methods is key to reliable SOC estimation. A dynamic, high-order equivalent circuit model, featuring two RC pairs in series with the battery's internal resistance, is employed to enhance parameter extraction. The values of the RC pairs are derived by solving equations that characterize the operational state... More >