Neural networks based nonlinear H∞ control for linear switched reluctance motor

H.Y. Li, Y.L. Liu, J. Wang, Y.K. Wong, Wai Lok Chan

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

Abstract

This paper is concerned with Hinfin control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, Hinfin tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external disturbance and NNs approximation error to a prescribed level. Furthermore, theoretical results are applied to a position tracking control of linear switched reluctance motor. Simulation studies are included to demonstrate the effectiveness of the method.
Original languageEnglish
Title of host publicationASCC 2009 : the proceedings of 2009 7th Asian Control Conference : Hong Kong Convention and Exhibition Centre, Hong Kong : August 27-29, 2009
PublisherIEEE
Pages796-801
Number of pages6
ISBN (Electronic)9788995605691
ISBN (Print)9788995605622
Publication statusPublished - 2009
EventAsian Control Conference [ASCC] -
Duration: 1 Jan 2009 → …

Conference

ConferenceAsian Control Conference [ASCC]
Period1/01/09 → …

Keywords

  • Hinfin control
  • Lyapunov methods
  • Linear motors
  • Machine control
  • Neurocontrollers
  • Nonlinear control systems
  • Position control
  • Reluctance motors
  • Stability
  • Uncertain systems

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