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http://dx.doi.org/10.7236/IJASC.2021.10.2.175

Improved BP-NN Controller of PMSM for Speed Regulation  

Feng, Li-Jia (Dept. of Energy Electrical Eng., Graduate School, Woosuk University)
Joung, Gyu-Bum (Dept. of Energy Electrical Eng., Graduate School, Woosuk University)
Publication Information
International journal of advanced smart convergence / v.10, no.2, 2021 , pp. 175-186 More about this Journal
Abstract
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 forthe 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.
Keywords
Improved BP Neural Network (BP-NN) Control Algorithm; Permanent Magnet Synchronous Motor (PMSM); Adaptive Gain Factor; Speed Regulation;
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