TY - JOUR
T1 - Adaptive sliding mode control of chaos in permanent magnet synchronous motor via fuzzy neural networks
AU - Nguyen, Tat Bao Thien
AU - Liao, Teh Lu
AU - Yan, Jun Juh
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
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U2 - 10.1155/2014/868415
DO - 10.1155/2014/868415
M3 - Article
AN - SCOPUS:84896132148
SN - 1024-123X
VL - 2014
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
M1 - 868415
ER -