Evaluating the Impact of Noise on Optimal LQR Control Methods in Enhancing the Performance of DC Motor Systems for Community

Abstract

In today’s fast-paced and ever-evolving world, technological advancements are rapidly transforming various sectors, and their impact is profoundly felt across multiple domains. The usefulness of technology and information is vast, with applications that touch almost every aspect of human life. As we witness these developments, the continuous progress in science becomes a key factor that drives innovation. By utilizing and refining existing knowledge, we can ensure that it functions optimally in addressing future challenges. In particular, the demand for electricity in industries is growing exponentially, necessitating well-distributed and efficient energy systems. One area where this need is crucial is in the optimization of electrical systems, specifically in propulsion engines, which play a significant role in community-based energy solutions. This research focuses on exploring the impact of noise on the optimization of control methods such as Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) when applied to DC motor systems. The goal is to investigate how these advanced control methods can be adapted for community-scale energy applications, ensuring efficiency and sustainability in energy distribution, especially in rural or underserved areas. By evaluating the effects of external noise on system performance, this study seeks to provide insights that can improve the reliability and effectiveness of DC motors used in renewable energy systems for local communities. The findings will contribute to the ongoing efforts to innovate and optimize technology for community empowerment and sustainable energy solutions.