神经网络在船舶柴油发电机转速控制应用

Application of Neural Network to Speed Control of Marine Diesel Generator

通过在船舶柴油发电机转速控制中的应用,将整理后的数据训练神经网络,建立了Elman神经网络,代替传统的PID控制算法,使训练好的Elman具有自适应功能,在船舶电力系统中代替PID控制器,实现了转速的自适应控制功能,并对Elman神经网络模型进行仿真测试。仿真结果表明该方法控制精度高,动、静态特性好,运用基于Elman神经网络的串行控制方法解决了船舶柴油发电机组系统的非线性控制问题。

The Elman neural network has been set up by applying of it to marine diesel generator speed control and training the neural network with the reduced data. It has replaced the traditional PID control algorithm, and the Elman after being trained has been provided with self-adaption function. It can replace the PID controller in marine electric system to realize self- adaption control function of the rotation speed. The simulation test for Elmanneural network model has been carried out. The simulation result shows that this method has high accuracy, good dynamic and static characteristics. Based on serial control method of the Elman neural net- work, non-linear control problem of the marine diesel generator system is solved.