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System identification and the modeling of sailing yachts.

机译:系统识别和帆船游艇建模。

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摘要

This research represents an exploration of sailing yacht dynamics with full-scale sailing motion data, physics-based models, and system identification techniques. The goal is to provide a method of obtaining and validating suitable physics-based dynamics models for use in control system design on autonomous sailing platforms, which have the capacity to serve as mobile, long range, high endurance autonomous ocean sensing platforms. The primary contributions of this study to the state-of-the-art are the formulation of a five degree-of-freedom (DOF) linear multi-input multi-output (MIMO) state space model of sailing yacht dynamics, the process for identification of this model from full-scale data, a description of the maneuvers performed during on-water tests, and an analysis method to validate estimated models. The techniques and results described herein can be directly applied to and tested on existing autonomous sailing platforms.;A full-scale experiment on a 23ft monohull sailing yacht is developed to collect motion data for physics-based model identification. Measurements include 3 axes of accelerations, velocities, angular rates, and attitude angles in addition to apparent wind speed and direction. The sailing yacht herein is treated as a dynamic system with two control inputs, the rudder angle, deltaR, and the mainsail angle, delta B, which are also measured. Over 20 hours of full scale sailing motion data is collected, representing three sail configurations corresponding to a range of wind speeds: the Full Main and Genoa (abbrev. Genoa) for lower wind speeds, the Full Main and Jib (abbrev. Jib) for mid-range wind speeds, and the Reefed Main and Jib (abbrev. Reef) for the highest wind speeds. The data also covers true wind angles from upwind through a beam reach.;A physics-based non-linear model to describe sailing yacht motion is outlined, including descriptions of methods to model the aerodynamics and hydrodynamics of a sailing yacht in surge, sway, roll, and yaw. Existing aerodynamic models for sailing yachts are unsuitable for control system design as they do not include a physical description of the sails' dynamic effect on the system. A new aerodynamic model is developed and validated using the full-scale sailing data which includes sail deflection as a control input to the system. The Maximum Likelihood Estimation (MLE) algorithm is used with non-linear simulation data to successfully estimate a set of hydrodynamic derivatives for a sailing yacht.;It is shown that all sailing yacht models will contain a second order mode (referred to herein as Mode 1A.S or 4B.S) which is dependent upon trimmed roll angle. For the test yacht it is concluded that for this mode when the trimmed roll angle is, roll rate and roll angle are the dominant motion variables, and for surge velocity and yaw rate dominate. This second order mode is dynamically stable for . It transitions from stability in the higher values of to instability in the region defined by. These conclusions align with other work which has also found roll angle to be a driving factor in the dynamic behavior of a tall-ship (Johnson, Miles, Lasher, & Womack, 2009).;It is also shown that all linear models also contain a first order mode, (referred to herein as Mode 3A.F or 1B.F), which lies very close to the origin of the complex plane indicating a long time constant. Measured models have indicated this mode can be stable or unstable. The eigenvector analysis reveals that the mode is stable if the surge contribution is 20%.;The small set of maneuvers necessary for model identification, quick OSLS estimation method, and detailed modal analysis of estimated models outlined in this work are immediately applicable to existing autonomous mono-hull sailing yachts, and could readily be adapted for use with other wind-powered vessel configurations such as wing-sails, catamarans, and tri-marans. (Abstract shortened by UMI.).
机译:这项研究代表了对具有完整航行运动数据,基于物理的模型和系统识别技术的航行游艇动力学的探索。目的是提供一种获取和验证适合用于自主航行平台的控制系统设计中的基于物理学的动力学模型的方法,该模型具有用作移动,远程,高耐久性的自主海洋传感平台的能力。这项研究对最新技术的主要贡献是制定了帆船运动动力学的五自由度(DOF)线性多输入多输出(MIMO)状态空间模型,从全面数据中识别该模型,对在水上测试期间执行的操作进行描述以及用于验证估计模型的分析方法。本文描述的技术和结果可以直接应用于现有的自主航行平台并在现有的自主航行平台上进行测试。开发了23英尺单壳帆船游艇的全面实验,以收集运动数据以进行基于物理的模型识别。除了视风速和风向以外,测量还包括3个加速度,速度,角速度和姿态角的轴。本文中的帆船游艇被视为具有两个控制输入(舵角δR和主帆角δB)的动态系统,这两个系统也已测量。收集了超过20个小时的完整航海运动数据,代表了三种风向配置,分别对应于不同的风速:风速较低的Full Main和Genoa(缩写为Genoa),风速较低的Full Main和Jib(缩写为Jib)。中等风速,而Reefed Main和Jib(简称Reef)则是最高风速。数据还涵盖了从上风到波束到达的真实风向角。概述了描述帆船运动的基于物理学的非线性模型,包括对帆船在喘振,摇摆,滚动和偏航。现有的用于航行游艇的空气动力学模型不适用于控制系统设计,因为它们没有包括帆对系统动态影响的物理描述。使用包括帆偏度作为系统控制输入的全尺寸航行数据,开发并验证了新的空气动力学模型。最大似然估计(MLE)算法与非线性仿真数据结合使用,可以成功地估计帆船游艇的一组流体动力学导数;表明所有帆船游艇模型都将包含二阶模式(在本文中称为模式1A.S或4B.S),具体取决于调整后的侧倾角。对于测试游艇,可以得出结论,对于该模式,当调整后的侧倾角为时,侧倾率和侧倾角是主要的运动变量,对于喘振速度和偏航率而言则占主导地位。该二阶模式对于而言是动态稳定的。它从较高的值的稳定性过渡到由定义的区域的不稳定性。这些结论与其他研究相吻合,其他研究也发现侧倾角是高船动力行为的驱动因素(Johnson,Miles,Lasher,&Womack,2009).;还表明,所有线性模型还包含一阶模式(在此称为模式3A.F或1B.F),非常靠近表示较长时间常数的复平面​​的原点。实测模型表明该模式可以稳定或不稳定。特征向量分析表明,如果喘振贡献为20%,则该模式是稳定的;该工作概述的模型识别所需的少量操作,快速OSLS估计方法以及对估计模型的详细模态分析可立即应用于现有自治系统单体帆船游艇,并且可以很容易地与其他风力动力船配置一起使用,例如机翼帆,双体船和三桅帆船。 (摘要由UMI缩短。)。

著录项

  • 作者

    Legursky, Katrina.;

  • 作者单位

    University of Kansas.;

  • 授予单位 University of Kansas.;
  • 学科 Engineering Marine and Ocean.;Engineering Aerospace.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 177 p.
  • 总页数 177
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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