Adaptive sliding mode control of chaos in permanent magnet synchronous motor via fuzzy neural networks

Tat Bao Thien Nguyen, Teh Lu Liao, Jun Juh Yan

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM) drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.

Original languageEnglish
Article number868415
JournalMathematical Problems in Engineering
Volume2014
DOIs
Publication statusPublished - 2014

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Engineering(all)

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