Sensorless Speed Control of Direct Current Motor by Neural Network

신경회로망을 이용한 직류전동기의 센서리스 속도제어

  • 강성주 (한국해양대학교 산업대학원) ;
  • 오세진 (한국해양대학교 기관시스템공학부 대학원) ;
  • 김종수 (한국해양대학교 부설 해사산업연구소)
  • Published : 2004.01.01

Abstract

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as speed detectors. but they increase cost and size of the motor and restrict the industrial drive applications. So in these days. many Papers have reported on the sensorless operation or DC motor(3)-(5). This paper Presents a new sensorless strategy using neural networks(6)-(8). Neural network structure has three layers which are input layer. hidden layer and output layer. The optimal neural network structure was tracked down by trial and error and it was found that 4-16-1 neural network has given suitable results for the instantaneous rotor speed. Also. learning method is very important in neural network. Supervised learning methods(8) are typically used to train the neural network for learning the input/output pattern presented. The back-propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

Keywords

References

  1. Analysis of Electric Machinery Paul C. Krause
  2. Power Electronics and AC Drives B.K.Bose
  3. IEEE Trans. Indus. Appli. v.IA-21 no.4 Microcomputer Control for Sensorless Brushless Motor K.Lizuka;H.Uzuhashi;M.Kano;T.Endo;K.Mohri
  4. IEEE Trans. On Ind. Appl. v.28 no.1 Brushless de motor control without position and speed sensors Nobuyuki Matsui;Masakane Shigyo
  5. IEEE Trans. Indus. Appli. v.28 no.3 Direct Self-Control on Inverter Fed Induction Machine: A Basis for Speed Control without Speed Measurement U.Baader;M.Depenbrock;G.Gierse
  6. IEEE Trans. Indus. Appli. v.31 no.3 Neural Network Based Estimation of Feedback Signals for a Vector-Controlled Induction Motor Drive M.G.Simoes;B.K.Bose
  7. IEEE Trans. On Ind. Appl. v.31 no.3 Identification and Control of Induction Machine Using Artificial Neural Networks M.T.Wishart;R.G.Harley
  8. Neuro-Fuzzy and Soft Computing J.S.R.Jang;C.T.Sun;E.Mizutani