Adaptive fuzzy-neural-network control for induction spindle motor drive

Faa Jeng Lin, Rong Jong Wai

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

An induction spindle motor drive using synchronous pulse-width modulation (PWM) and dead-time compensatory techniques with an adaptive fuzzy-neural-network controller (AFNNC) is proposed in this study for advanced spindle motor applications. First, the operating principles of a new synchronous PWM technique and the circuit of dead-time compensator are described in detail. Then, since the control characteristics and motor parameters for high-speed-operated induction spindle motor drive are time varying, an AFNNC is proposed to control the rotor speed of the induction spindle motor. In the proposed controller, the induction spindle motor-drive system is identified by a fuzzy-neural-network identifier (FNNI) to provide the sensitivity information of the drive system to an adaptive controller. The backpropagation algorithm is used to train the FNNI online. Moreover, the effectiveness of the proposed induction spindle motor-drive system is demonstrated using some simulated and experimental results.

Original languageEnglish
Pages (from-to)507-513
Number of pages7
JournalIEEE Transactions on Energy Conversion
Volume17
Issue number4
DOIs
StatePublished - Dec 2002

Keywords

  • Adaptive control
  • Dead-time compensator
  • Fuzzy neural network
  • Induction spindle motor
  • Synchronous pulse-width modulation

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