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Parameter Identification of the Maneuvering Model for Large Vessel Sailing in Different Conditions

机译:不同条件下大型船舶航行操纵模型的参数辨识

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The ship autopilot is designed based on the exact model to ensure high security and good performance. In order to obtain exact parameters of the model in different environment conditions, this paper proposes a method which identifies the parameters in calm and severe sea condition respectively. In calm sea condition, it identifies the steerability parameter K through constant rudder angle maneuvering at first. After the constant rudder angle maneuvering, it identifies the time parameter T through zero rudder angle maneuvering. In severe sea condition, the ship course is interfered by strong wave interference and the identification approach used in calm sea is ineffective. It considers the ship manipulation as an ARMAX model and uses prediction-error approach to identify the transfer function of the ship maneuvering. Finally, it tests performances of the proposed identification algorithm through some experiments, and the results show that the proposed algorithm adapts to different conditions.
机译:船舶自动驾驶仪是根据精确模型设计的,以确保高安全性和良好的性能。为了在不同的环境条件下获得模型的精确参数,本文提出了一种方法,其分别识别平静和严重的海洋状况中的参数。在平静的海洋状况下,它首先通过恒定的舵角操纵来识别测量性参数k。在恒定的舵角操纵之后,它识别通过零舵角操纵的时间参数t。在严重的海洋状况下,船舶课程受强烈的波浪干扰干扰,平静海洋中使用的识别方法无效。它将船舶操作视为ARMAX模型,并使用预测误差方法来识别船舶操纵的传递函数。最后,它通过一些实验测试所提出的识别算法的性能,结果表明,所提出的算法适应不同的条件。

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