Earticle

초록

영어

We have studied the speed regulation of the permanent magnet synchronous motor (PMSM) servo system in this paper. To optimize the PMSM servo system's speed-control performance with disturbances, a non-linear speed-control technique using a back-propagation neural network (BP-NN) algorithm for the controller design of the PMSM speed loop is introduced. To solve the slow convergence speed and easy to fall into the local minimum problem of BP-NN, we develope an improved BP-NN control algorithm by limiting the range of neural network outputs of the proportional coefficient Kp, integral coefficient Ki of the controller, and add adaptive gain factor β, that is the internal gain correction ratio. Compared with the conventional PI control method, our improved BP-NN control algorithm makes the settling time faster without static error, overshoot or oscillation. Simulation comparisons have been made for our improved BP-NN control method and the conventional PI control method to verify the proposed method's effectiveness.

목차

Abstract
1. Introduction
2. Improved BP-NN Controller Algorithm for PMSM
2.1 Mathematical Model of PMSM
2.2 BP Neural Network Controller Algorithm
2.3 Model Establishment
3. Simulation Results
3.1 Starting Up at Medium or High Reference Speed
3.2 Starting Up at Low Reference Speed
3.3 Starting Up Transient Response at High Reference Speed with Large Load Lorque
4. Conclusion
Acknowledgement
References

키워드

저자

• Li-Jia Feng [ Ph.D Course Student, Dept. of Energy Electrical Eng., Graduate School, Woosuk University, Korea ]
• Gyu-Bum Joung [ Professor, Dept. of Energy Electrical Eng., Graduate School, Woosuk University, Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380