Performance Optimization of BSG-23 DC Motors Using Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) Approaches

Abstract

DC motors have become a critical component in a variety of industrial and technological applications due to their reliability and flexibility in speed and torque control. To support optimal performance, a precise and efficient controller design is required. Automatic control systems play an essential role in supporting the needs of modern society, especially in countries with advanced civilizations. Specific applications include control of spacecraft systems, guided missiles, satellites, aircraft control systems, to various industrial processes such as control of pressure, temperature, flow, humidity, and friction during the production process. In the last decade, the issue of optimal control has become a major concern due to the increasing need for more efficient, stable, and reliable systems. Control system optimization integrates performance and technical specification limits to produce a system that works optimally according to its physical constraints. When dealing with an optimal control system, the main challenge is to formulate decision rules that minimize deviations from the ideal conditions of the system, even under conditions of load or disturbance. Linear Quadratic Regulator (LQR) is one of the optimal control methods that has been widely used in various applications. In addition, Linear Quadratic Tracking (LQT) is an approach that complements LQR to ensure the system can accurately follow the reference trajectory. This research focuses on optimizing the performance of BSG-23 DC Motors using a combination of LQR and LQT methods. The simulation results show that this approach is able to improve stability, speed up response time, and significantly reduce overshoot. This research makes an important contribution to the development of more efficient and adaptive DC motor control systems for various engineering and industrial applications.