Simulation Analysis of System Optimization Using an EC-Max 40 Type DC Motor Plant
DOI:
https://doi.org/10.71225/jstn.v2i3.107Keywords:
DC Motor, LQR, LQT, Noise, OptimizationAbstract
A control system functions to regulate one or more variables, ensuring they remain at specific values or within desired limits. The primary aim is to achieve optimal system performance through effective control strategies. In this study, system optimization is explored within a closed-loop configuration using a DC motor as the plant. The motor selected for this analysis is the EC-Max 40, a direct current motor that converts electrical energy into mechanical motion. Utilizing the motor's datasheet, a first-order mathematical model is developed and implemented in Matlab Simulink for simulation purposes. The system design incorporates both Linear Quadratic Regulator (LQR) and Linear Quadratic Tracker (LQT) methods to evaluate and compare their performance. The analysis focuses on the step response of the system observing how the output behaves in response to input variations both under ideal conditions and in the presence of noise. The simulations reveal that both LQR and LQT methods produce similarly effective results; however, the LQT approach demonstrates a faster convergence to stability compared to the LQR method.
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