摘要
当船舶在海湾、海峡等狭窄海域行驶时,对于船舶航向控制器的可靠性和灵活性均有较高的要求,由于船舶模型的参数受到航速和载重量的影响,因而无法保证航向控制的精确性。本文提出一种船舶模型控制与动态神经网络相结合的方法,提高船舶航向控制器的控制精度和可靠性。设计一种零稳态误差控制器对船舶航向进行控制,同时利用模糊神经网络确定闭环控制系统的极点,并用仿真证明本文提出的方法具有较高的精确性和可靠性。
When the ships are in the gulf or the narrow waters such as channel,reliability and flexibility for ship course controller have higher requirements. Because that the parameters of ship model are under the influence of the speed and load,there is no guarantee on the accuracy of course control. This paper puts forward a model of ship control combining dynamic neural network to improve the control precision and reliability of ship course controller. A zero steady-state error controller is designed to control the ship course,at the same time,a fuzzy neural network is used to determine the poles of a closed loop control system,and the simulation proves that the proposed method has higher accuracy and reliability.
出处
《舰船科学技术》
北大核心
2015年第1期174-177,共4页
Ship Science and Technology
基金
2009浙江省科技厅面上资助项目(2009C31165)
关键词
航向控制
模糊神经网络
闭环控制系统
ship course control
fuzzy neural network
closed loop control system
