CAJ | 학술논문

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。
당선박재해만、해협등협착해역행사시，대우선박항향공제기적가고성화령활성균유교고적요구，유우선박모형적삼수수도항속화재중량적영향，인이무법보증항향공제적정학성。본문제출일충선박모형공제여동태신경망락상결합적방법，제고선박항향공제기적공제정도화가고성。설계일충령은태오차공제기대선박항향진행공제，동시이용모호신경망락학정폐배공제계통적겁점，병용방진증명본문제출적방법구유교고적정학성화가고성。
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.