模拟退火遗传算法在煤矿主扇控制中的应用

An Application Of GA With SA To Controlling Main Fan Of Mine

根据矿井通风系统的工作特点，采用适用于非线性时变系统的神经网络方法对煤矿主扇风机进行实时控制。介绍了煤矿主扇风机的控制原理，提出了求解全局最优解的神经网络学习方法 - 模拟退火遗传算法，并给出了算法的实现过程。系统采用无环流交-交变频控制方案、应用无速度传感器的矢量控制技术对拖动煤矿主扇风机的感应电动机进行控制。

According to the features of ventilation systems in coal mines, a neural network method that is suitable for nonlinear and time-dependent systems is applied to control the main ventilator of coal mines in real time, the principle of controlling a main ventilation fan is also explained in detail. Genetic algorithm combining with simulated annealing, a neural network method for overall optimized solution is presented with the solving process given in this paper. The system is designed as circulation absent and A-A VF controlled one, in which a responsive motor driving the main ventilation fan is controlled in a vector control technology without speed sensor.