摘要
船舶自动舵控制十分复杂,再加其它因素的干扰,使得单一神经网络或者PID控制无法对船舶自动舵进行高精度控制,而且船舶自动舵控制速度慢,为了改善船舶自动舵控制效果,利用BP神经网络和PID控制的优点,设计了BP神经网络和PID相融合的船舶自动舵控制方法。首先分析船舶自动舵控制原理,然后初始化PID参数的范围,并采用BP神经网络获取PID控制器的3个参数最优值,从而实现船舶自动舵控制,最后在Matlab平台实现了的船舶自动舵控制仿真模拟实验。结果表明,本文方法可以对船舶自动舵变化趋势进行很好的跟踪和控制,获得了高精度的船舶自动舵控制结果,而且船舶自动舵控制速度快,能够适合船舶自动舵的实时性变化特性,具有较强的抗干扰能力,具有一定的推广价值。
The control of ship automatic rudder is very complicated,and the disturbance of other factors makes it impossible for single neural network or PID control to control ship automatic rudder with high precision,and the control speed of ship automatic rudder is slow.In order to improve the control effect of ship automatic rudder,the ship automatic rudder control Method is proposed based on BP neural network and PID control which uses the advantages of BP neural network and PID control..Firstly,the principle of ship automatic rudder control is analyzed,then the range of PID parameters is initialized,and the BP neural network is used to obtain the optimal values of three parameters of the PID controller,so as to realize the speed of ship automatic rudder control.Finally,the simulation experiment of ship automatic rudder control is realized on Matlab platform.The results show that this method can track and control the changing trend of ship’s automatic rudder very well,and obtain high-precision control results of ship’s automatic rudder.Moreover,the speed of ship’s automatic rudder control is fast,and it can adapt to the real-time change characteristics of ship’s automatic rudder.It has strong anti-interference ability and has certain popularization value.
作者
张静文
张庆松
ZHANG Jing-wen;ZHANG Qing-song(Chongqing Creation Vocational College,Chongqing 402160,China)
出处
《舰船科学技术》
北大核心
2019年第16期124-126,共3页
Ship Science and Technology
