Speed-sensorless vector control of an induction motor using neural network speed estimation

Seong Hwan Kim, Tae Sik Park, Ji N. Yoo, Gwi Tae Park

Research output: Contribution to journalArticlepeer-review

153 Citations (Scopus)


In this paper, a novel speed estimation method of an induction motor using neural networks (NNs) is presented. The NN speed estimator is trained online by using the error backpropagation algorithm, and the training starts simultaneously with the induction motor working. The estimated speed is then fed back in the speed control loop, and the speed-sensorless vector drive is realized. The proposed NN speed estimator has shown good performance in the transient and steady states, and also at either variable-speed operation or load variation. The validity and the usefulness of the proposed algorithm are thoroughly verified with experiments on fully digitalized 2.2-kW induction motor drive systems.

Original languageEnglish
Pages (from-to)609-614
Number of pages6
JournalIEEE Transactions on Industrial Electronics
Issue number3
Publication statusPublished - 2001 Jun


  • Induction motor
  • Neural networks
  • Speed estimation
  • Speed-sensorless vector control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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