Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (6): 2280-2286.doi: 10.13229/j.cnki.jdxbgxb20200580

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PID control based on BP neural network optimized by Q⁃learning for speed control of BLDCM

Hong-zhi WANG1,2(),Ting-ting WANG1,Huang-shui HU3(),Xiao-fan LU3   

  1. 1.School of Mechatronic Engineering，Changchun University of Technology，Changchun 130012，China
    2.School of Computer Science and Engineering，Changchun University of Technology，Changchun 130012，China
    3.School of Computer Science and Engineering，Jilin University of Architecture and Technology，Changchun 130114，China
  • Received:2020-07-30 Online:2021-11-01 Published:2021-11-15
  • Contact: Huang-shui HU E-mail:wanghongzhi@ccut.edu.cn;huhs08@163.com

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Abstract:

In order to improve the stability of Brushless DC Motor (BLDCM), a method of Q-learning algorithm optimized BP neural network PID controller (QBP-PID) is proposed. QBP-PID uses BP Neural Network (BPNN) to adjust the PID gain, and then optimizes the key weights in BPNN by modifying the weight momentum factor through Q-learning. Therefore the controller has better learning and online correction abilities, and the BLDCM can achieve better control effect. The simulation results show that QBP-PID has better adaptive ability, anti-interference ability and stronger robustness than the traditional PID, Fuzzy PID (Fuzzy-PID) and BP neural network PID (BP-PID) controllers.

Key words: control theory and control engineering, brushless direct current motor（BLDCM）, proportion integration differentiation controller, back propagation neural network（BPNN）, Q-learning

CLC Number: 

  • TP273

Fig.1

Equivalent circuit of BLDCM"

Fig.2

Control system of BP-PID"

Fig.3

Schematic diagram of Q-learning algorithm"

Fig.4

Framework of QBP-PID speed controller"

Table 1

Simulation parameters of BLDCM"

参 数数值
额定电压/V470
额定电流/A50
定子电阻相/Ω3
定子相电感/H0.001
电压常数/（V·r-1·min）0.1466
转矩常数/（N·m·A-1）1.4
转动惯量/（kg·m2·rad-1）0.0008
阻力因子/（N·m·s·rad-1）0.001
极对数P4

Fig.5

Speed response with no load"

Fig.6

Speed response with load"

Fig.7

Speed response with various speed"

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