Research step of PID control method of stepper motor based on improved fuzzy control algorithm

Authors

  • Zichi Zhang North China University of Science and Technology image/svg+xml
  • Xiangding Meng North China University of Science and Technology image/svg+xml
  • Yilei Kou North China University of Science and Technology image/svg+xml

DOI:

https://doi.org/10.4108/eetsis.5205

Keywords:

PID control, Improved fuzzy control algorithm, management systems, Theory

Abstract

The significance of PID control within the management system of stepper motors is noteworthy; nonetheless, it is worth noting that stepper motors are susceptible to issues such as low power, step loss, and vibration. The conventional Proportional-Integral-Derivative (PID) control method is insufficient in addressing the control challenge specific to stepper motor management systems. Hence, this research work presents an enhanced fuzzy control method that integrates the principles of fuzzy control theory with traditional PID control theory. The integration of fuzzy control into the P ID control is undertaken to create a fuzzy controller that satisfies the demands of stepper motor control. Additionally, the division of indices is conducted in accordance with the specifications of the fuzzy controller in order to mitigate the disruptive elements of PID control. then, the use of fuzzy control rules is employed to achieve control over the stepper motor, resulting in the development of an enhanced scheme that is then subjected to rigorous validation. The present study employs a MATLAB simulation to compare the performance of the enhanced fuzzy control algorithm with that of the P-ID control method. The results demonstrate that the improved fuzzy control algorithm significantly enhances the stability and dynamic performance of the stepper motor. Superior to traditional Proportional-Integral-Derivative (PID) control.

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Published

26-02-2024

How to Cite

1.
Zhang Z, Meng X, Kou Y. Research step of PID control method of stepper motor based on improved fuzzy control algorithm. EAI Endorsed Scal Inf Syst [Internet]. 2024 Feb. 26 [cited 2024 Apr. 20];. Available from: https://publications.eai.eu/index.php/sis/article/view/5205

Issue

Section

Short communications