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为更快更好地控制船舶在预定航线上航行,提出一种船舶航向在线自学习模糊神经网络智能控制方法.模糊子集处理船舶控制中的不确切信息,通过神经网络训练模糊推理系统中的参数,旨在把模糊推理和神经网络融合,使船舶航向智能控制器具有在线自学习功能.该方法能实时控制风流扰动下作为非线性时变系统的船舶而无须依赖船舶运动数学模型.模拟试验结果表明,即使在有环境扰动情况下,该方法也能很好地控制具有很大惯性船舶的航向.
In order to control the ship sailing on the scheduled route faster and better, an intelligent self-learning fuzzy neural network control method for ship course is proposed. The fuzzy subset is used to process the inaccurate information in the ship’s control, and the neural network is used to train the fuzzy inference system Which aims to integrate fuzzy inference and neural network to make the ship course intelligent controller have online self-learning function. This method can control ship as a nonlinear time-varying system in real time under disturbance of wind flow without relying on mathematical model of ship motion. The results show that this method can well control the course of a ship with a large inertia even in the presence of environmental disturbances.