Analysis of Circuit with LQR and LQT Control Systems on DC Motor Type C34-L70 with Noise

Abstract

The rapid advancement of technology to meet various human needs has significantly facilitated various aspects of daily life, including industrial processes. One notable technological innovation in this regard is the DC motor, which serves as a critical actuator in numerous industrial applications. DC motors are valued for their simplicity, precision, and controllability, making them essential in automation, robotics, and other mechanical systems. However, despite their advantages, a common challenge encountered with DC motors is the inability of the output to consistently reach the desired target or setpoint. This issue is often attributed to various factors such as system instability, external disturbances, and the limitations of the control methods used. To mitigate these challenges, system optimization strategies are implemented to improve the performance of DC motors and ensure they can achieve precise and reliable outputs. System optimization is vital in overcoming the inherent limitations of DC
motors, particularly when external factors, such as noise, affect the system's performance. Noise, or external disturbances, can significantly impact the output of a DC motor, causing fluctuations and reducing its efficiency. To address these issues, various control techniques, such as Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) controllers, have been explored in this paper. These methods are designed to stabilize the motor's performance by minimizing errors between the actual output and the desired setpoint. LQR and LQT are advanced control strategies that help optimize the system by adjusting control inputs to achieve better performance, particularly in environments with high levels of disturbance or noise. In this study, noise is
introduced into the DC motor system using different circuits, and its effects on the output are carefully analyzed. The noise is applied to each output through various configurations, and the resulting disturbances are evaluated to understand their impact on the motor's performance. The findings from these experiments are crucial in identifying the specific factors that influence the motor's behavior under noisy conditions. The goal is to minimize the interference caused by noise, thereby preserving the motor's ability to maintain high-quality performance. The application of LQR and LQT controllers is tested to see how effectively they can suppress the negative effects of noise and enhance the motor's response to disturbances, ensuring it can still reach the target output with minimal deviation. The investigation into the impact of noise on DC motors is essential for improving the reliability and efficiency of these systems, especially in industrial environments where noise and disturbances are common. By
implementing advanced control methods such as LQR and LQT, it is possible to optimize the motor's performance and achieve greater precision in its operation. The results of this study will contribute to the development of more robust control systems that can mitigate the impact of external disturbances, ensuring that DC motors continue to perform efficiently and accurately in real-world applications. Ultimately, this research provides valuable insights into the importance of noise management and the role of control strategies in enhancing the performance and reliability of DC motors.