Application of LQR and LQT Control Methods for Optimization of DC Motor Control Systems Based on MATLAB Simulink in the Energy Efficiency Improvement Program for Home Industry Players

Abstract

The presence of a controller in a control system plays a significant role in determining the behavior of the system. Fundamentally, this is due to the inherent properties of the system components, which cannot be altered. Consequently, the system's behavior can only be modified by introducing an additional system component, namely the controller. Modern control systems, enhanced with optimization techniques, have evolved into advanced modern control theories and robust control systems widely applied in industrial settings. Optimization and control systems primarily utilize frameworks such as MIMO (Multiple Input Multiple Output), SIMO (Single Input Multiple Output), MISO (Multiple Input Single Output), and SISO (Single Input Single Output), which are built on the principles of diversity and adaptability. This research focuses on applying Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) methods in optimizing DC motor control systems, using MATLAB Simulink to support energy efficiency programs for small-scale industries. The integration of these control methods is not only aimed at improving system performance but also at addressing the needs of micro-entrepreneurs through practical and implementable solutions, fostering social and economic development. The study findings contribute to community service initiatives by introducing energy-efficient technologies that empower small business owners to adopt sustainable practices. This aligns with the broader goal of bridging technological advancements with societal impact, providing a pathway for scalable and practical applications in real-world settings.