采用遗传算法的直接转矩控制系统仿真研究

The Simulation Research for Direct Torque Control System Using Genetic Algorithms

直接转矩控制 (DTC)是一种高性能的控制方法 ,它的关键部件是状态选择器 用神经网络来模拟传统异步电动机DTC系统的状态选择器 ,并采用遗传算法训练该神经网络 ,然后用训练好的神经网络代替状态选择器 ,并进行了仿真研究 。

Direct torque control (DTC) is a high performance control method. The key component of DTC is the state selector. In this paper, the neural network is used to simulate the state selector of the conventional DTC system for asynchronous motor by using a genetic algorithm to train the neural network. The simulations are obtained by using the trained state selector neural network instead of the conventional DTC. The simulation results are satisfactory.