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

研究成果: Article同行評審

20 引文 斯高帕斯(Scopus)

摘要

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.

原文English
文章編號868415
期刊Mathematical Problems in Engineering
2014
DOIs
出版狀態Published - 2014

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Engineering(all)

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