Comparison of System Optimization Methods: LQR vs. LQT on the Output Response of IG-42CRGM DC Motor
DOI:
https://doi.org/10.71225/jstn.v2i4.99Keywords:
Optimal control, Linear Quadratic Regulator, DC MotorAbstract
DC motors are widely utilized in industrial applications for their reliability and efficiency. To optimize their performance, it is crucial to employ control systems supported by mathematical modeling to predict motor responses under varying conditions. This study investigates the first- and second-order models of DC motors and examines the impact of internal disturbances (noise) on system performance. The output responses of two DC motors, the 42BLFX02 and Maxon EC-I 40 (70W), are compared under both undisturbed and noisy conditions using simulations. The results reveal that the second-order model offers a more stable response and better aligns with the desired target compared to the first-order model. Furthermore, the application of the Linear Quadratic Regulator (LQR) control method significantly enhances the speed and accuracy of reaching the motor set point. However, when noise is introduced, the LQR method fails to maintain stability, and the motor's output starts to mirror the disturbance pattern. These findings highlight that while LQR is effective under ideal conditions, its performance diminishes when exposed to disturbances. Therefore, additional strategies are necessary to ensure stability and optimal performance in real-world conditions, particularly in environments with significant noise or disturbances.
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