Design of Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) Methods for DC Motor Control in Community Empowerment Systems by Taking into Account the Impact of Noise and No Noise
Keywords:
Electric Motor, Control System, Simulink, Community Empowerment, Linear Quadratic Regulator (LQR), Linear Quadratic Tracking (LQT)Abstract
Electric motors serve as actuators that convert electrical energy into mechanical energy, making them a critical component in various mechanical drive systems. Due to their essential function, electric motors are widely used in both industrial and community-based applications. In the context of community empowerment, especially in rural or underserved areas, the effective control and monitoring of electric motors can significantly enhance the productivity of local industries such as small-scale manufacturing, crafts, or agriculture. One of the key aspects of using electric motors is the control system, which plays a crucial role in regulating, monitoring, and analyzing the speed and motion of the motor. To ensure efficient operation, a telemetry system or interface is necessary to display graphical or visual representations of the motor's movement, allowing for real-time data acquisition and control. This system should be tailored to the needs of the community, optimizing energy use and improving motor performance. Simulink, a widely used software tool, provides an effective platform for modeling, simulating, and controlling motor dynamics. It allows for the design and analysis of control strategies, including the implementation of Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) methods, which can be applied to control electric motor systems under different conditions, such as those with or without noise interference. This research aims to develop a robust control system using LQR and LQT methods for DC motors, focusing on their application in community empowerment programs. The study will assess the impact of these control methods on the performance and efficiency of electric motors, taking into account the challenges posed by noise and other environmental factors. The results of this research have the potential to contribute significantly to community-based industrial applications by providing a practical and accessible solution for local enterprises to enhance motor performance and reduce operational costs.