scholarly journals Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Tat-Bao-Thien Nguyen ◽  
Teh-Lu Liao ◽  
Jun-Juh Yan

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.

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881527 ◽  
Author(s):  
Xudong Liu ◽  
Ke Li

A novel speed control method based on sliding mode control and disturbance observer is studied for permanent magnet synchronous motor drives. Different from the conventional speed and current cascade control structure in the field-oriented vector control, the new controller adopts the single-loop control structure, in which the speed and quadrate axes current controllers are combined together. First, a multiple-surface sliding mode controller is designed for the speed control system of permanent magnet synchronous motor. Although the sliding mode controller has the strong robustness for the matched disturbance in the system, it still cannot deal with mismatched disturbance effectively, such as external load disturbance and some parameter variations. Thus, the disturbance observer is introduced to estimate the disturbance in the motor, which is designed by combining the proposed sliding mode controller. Finally, the effectiveness is tested under various conditions by both simulation and experiment. The results show that the designed controller has the fast transient response and robustness under different operating conditions.


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