基于神经网络农用感应电动机直接转矩控制

    Agricultural Induction Motor Direct Torque Control Using Neural Networks

    • 摘要: 提出了基于神经网络的直接转矩控制方法,并应用到农用感应电动机的控制上。采用Levenberg优化方法进行网络训练,用神经网络代替了传统的开关状态的选择,实现交流电机的直接转矩控制。基于MATLAB对系统进行了仿真研究,结果表明,该方法和传统方法效果基本一致,具有较好的控制和运行性能,是研究运动控制的一种新方法。

       

      Abstract: In this paper, a novel approach to direct torque control to control the induction motor is presented. This method is based on the theory of the N-N algorithm. The learning arithmetic of Levenberg-Marquardt is used. The Neural Networks replace the choice of switching states. With MATLAB, the simulation is conducted, and the results show that the direct torque control system using this method has the same performance as conventional direct torque control. This motivates further research in the application of neural networks to new types of controllers in motor drive industry.

       

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