基于BP神经网络PID的舰船水下静电场防护控制的研究  

Research on Ship's Underwater Electrostatic Field Protection Based on BP Neural Network PID

作　　者：张济平 柳懿[1] 王向军[1] Zhang Jiping;Liu Yi;Wang Xiangjun(College of Electrical Engineering,Naval University of Engineering,Wuhan 430033,China)

机构地区：[1]海军工程大学电气工程学院,武汉430033

出　　处：《船电技术》2020年第9期40-44,共5页Marine Electric & Electronic Engineering

摘　　要：舰船的电场信号已经成为舰船的目标探测信号之一,所以水下静电场防护直接影响舰船作战时的隐身性能。本文基于外加补偿电流的方法,通过Simulink软件,分别采用常规PID控制与神经网络优化PID控制,进行补偿电流的输出比较。仿真结果表明,BP神经网络算法优化PID后的控制电流,超调量明显减小,稳定所需时间也明显缩短。接下来进行船模的试验验证,试验结果表明,神经网络优化后的PID控制在船模水下静电场防护方面效果更好。The electric field signal of the ship has become one of the ship's target detection signals,so the protection of the underwater electrostatic field directly affects the stealth performance of the ship in combat.Based on the method of adding compensation current,the conventional PID control and neural network optimized PID control are used to compare the output of compensation current through Simulink software.Simulation results show that the BP neural network algorithm optimizes the control current afte r PID,the overshoot is significantly reduced,and the time required for stabilization is also significantly reduced.And The test verification of the ship model show that the PID control optimized by the neural network is more effective in protecting the ship's underwater electrostatic field.

关 键 词：舰船静电场防护 常规PID 控制 BP 神经网络PID 控制 仿真分析 船模试验 

分 类 号：U674.703.7[交通运输工程—船舶及航道工程]