A back-stepping neural network control scheme for PM synchronous motors

J. Wang, K. M. Tsang, Chow Norbert Cheung

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Focusing on the seriously nonlinear problem and unknown or uncertain parameters, a backstepping control method based on neural networks is proposed to realize the multi-object position control of PM synchronous motors. Neural networks in the scheme are used to solve the contradiction between backstepping control and unmatched conditions of systems. A special weight online tuning method is proposed in this paper, and an off-line training phase is not required. The method does not require the system parameters to be exactly known, and the system is robust. The simulation results show that, the proposed method is effective.
Original languageEnglish
Title of host publication5th International Conference on Power Electronics and Drive Systems, PEDS 2003 - Proceedings
PublisherIEEE
Pages728-732
Number of pages5
Volume1
ISBN (Electronic)0780378857
DOIs
Publication statusPublished - 1 Jan 2003
Event5th International Conference on Power Electronics and Drive Systems, PEDS 2003 - Novotel Apollo Hotel, Singapore, Singapore
Duration: 17 Nov 200320 Nov 2003

Conference

Conference5th International Conference on Power Electronics and Drive Systems, PEDS 2003
Country/TerritorySingapore
CitySingapore
Period17/11/0320/11/03

Keywords

  • Backstepping
  • Neural Networks
  • PMSM Position control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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