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Information Technology Journal
  Year: 2010 | Volume: 9 | Issue: 7 | Page No.: 1440-1448
DOI: 10.3923/itj.2010.1440.1448
 
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Neural Network Sliding Mode based Current Decoupled Control for Induction Motor Drive

Peng Kang and Zhao Jin

Abstract:
This study deals with the problem of stator currents coupling effect in induction motor drives. In field oriented control, d-axis stator current and q-axis stator current should be regulated independently. However, the stator currents in d-q synchronously rotating reference frame are not naturally decoupled, therefore, a new control scheme for current control is proposed that utilizes Sliding Mode Control (SMC) and Radial Basis Function Neural Network (RBFNN) to achieve the decoupling without considerable chattering. In this control strategy, a RBFNN controller replaces the discontinuous part of the sliding mode controller to eliminate undesired chattering of conventional sliding mode controller. The decoupling method in this study uses two RBFNN sliding mode controllers to regulate d-axis stator current and q-axis stator current, respectively. Finally, simulation results of the proposed scheme have presented perfect performances, such as perfect decoupling, strong robustness and reduced chattering, in comparison with proportional-integral controller and sliding mode controller.
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How to cite this article:

Peng Kang and Zhao Jin, 2010. Neural Network Sliding Mode based Current Decoupled Control for Induction Motor Drive. Information Technology Journal, 9: 1440-1448.

DOI: 10.3923/itj.2010.1440.1448

URL: https://scialert.net/abstract/?doi=itj.2010.1440.1448

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