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研究生: 楊淳淯
Yang, Chun-Yu
論文名稱: 應用模糊控制於剛性翼帆船迎風航行策略之研究
Research on the Application of Fuzzy Control to Windward Sailing Strategies of Rigid Wind Sailboat
指導教授: 王舜民
Wang, Shun-Min
學位類別: 碩士
Master
系所名稱: 工學院 - 系統及船舶機電工程學系
Department of Systems and Naval Mechatronic Engineering
論文出版年: 2025
畢業學年度: 113
語文別: 中文
論文頁數: 103
中文關鍵詞: 剛性翼帆帆船航向推算法模糊控制迎風策略
外文關鍵詞: Rigid-Wing Sail, Sailboat, Dead Reckoning, Fuzzy Control, Upwind Sailing Strategy
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  • 本研究旨在開發一套適用於自主無人帆船之剛性翼帆控制系統,並結合模糊邏輯控制以實現穩定且高效的迎風航行策略。系統採用由美國國家航空諮詢委員會(National Advisory Committee for Aeronautics,NACA)所設計的NACA0012對稱翼型設計剛性翼帆,搭配具壓載功能之龍骨結構強化船體穩定性。硬體方面整合GPS、陀螺儀、風速計與磁性編碼器等感測模組,以NI myRIO為控制核心,透過LabVIEW平台執行多輸入多輸出(MIMO)模糊控制器。控制輸入涵蓋航向誤差、航線偏移量及船速,輸出為動態調整之舵角與翼帆角度指令,提升系統對變動環境的即時反應與導航精準度。
    模糊控制技術具備不須精確數學模型的優勢,可透過語意規則應對非線性、時變與不確定系統,克服傳統PID控制在海況變化劇烈時的不穩定問題。五項實驗設計包括:航向追蹤實驗、拉回實驗、迴旋實驗、Z型實驗及路徑點追蹤實驗,驗證穩定性與誤差修正能力、確認載具可從偏航狀態回歸目標線、測試最小轉彎半徑與控制響應、評估換舵操作的策略表現以及驗證多段連續導航能力。各項實驗結果顯示:MIMO模糊控制器能針對不同速度自動調節操控策略,使航向誤差穩定收斂於5°以內,航線偏移量平均小於1m內,展現高度導航精準度與回正能力。
    迎風航行實驗部分,實測於±30⁰、±45⁰與±60⁰三種迎風角度下進行比較,結果顯示:±60⁰風角下,由於與真風角夾角最大,所以船速/風速比值最高,展現最佳推進效率;±30⁰風角下航行距離最短所以航行時間最短,適合快速換向航行;±45⁰角則整體效率相對較差。此外,龍骨設計有效抑制大風下的橫搖與平擺,提升整體穩定性。剛性翼帆相較傳統軟帆在靠近無法航行區域仍能維持穩定推力,展現優異的空氣動力性能與操作穩定性。
    綜上所述,本研究成功建構一套整合感測、自主控制與航行策略之剛性翼帆船平台,並透過多輸入模糊控制器實現對複雜海況之穩定導航與靈活響應。其成果對臺灣自主無人帆船、綠色海洋科技與智能船舶技術具有前瞻價值,未來可應用於長時間環境監測、海上觀測與低碳航行任務。

    This study aims to develop a control system for a rigid-wing sail applicable to autonomous unmanned sailboats, integrating fuzzy logic control to enable stable and efficient upwind sailing strategies. The system adopts a rigid wing sail based on the NACA 0012 symmetric airfoil, originally developed by the National Advisory Committee for Aeronautics (NACA), and incorporates a ballast-equipped keel structure to enhance vessel stability. The hardware integrates sensors including GPS, gyroscope, anemometer, and magnetic encoders, with NI myRIO serving as the control core. A multi-input multi-output (MIMO) fuzzy controller is implemented on the LabVIEW platform. The controller takes heading error, cross-track deviation, and vessel speed as inputs and outputs dynamically adjusted rudder and sail angle commands, improving real-time responsiveness and navigational accuracy in dynamic environments.
    Fuzzy control offers the advantage of operating without requiring an exact mathematical model and can address nonlinear, time-varying, and uncertain systems through linguistic rule-based inference. This overcomes the instability issues often encountered with traditional PID control in rapidly changing sea conditions. Five experimental designs were conducted: heading tracking, return-to-course, turning radius, zigzag maneuvering, and waypoint path-following experiments. These tests were used to verify system stability and error correction capability, assess the vessel’s ability to return to its intended trajectory after deviation, determine the minimum turning radius and control responsiveness, assess tacking strategies, and demonstrate continuous multi-segment navigation performance. The experimental results showed that the MIMO fuzzy controller could autonomously adjust control strategies based on vessel speed, maintaining heading errors within 5° and average cross-track errors within 1 meter, demonstrating high navigational accuracy and effective course correction.
    In the upwind sailing experiments, three apparent wind angles—±30°, ±45°, and ±60°—were tested. Results indicated that at ±60°, the largest apparent wind angle produced the highest boat-to-wind speed ratio, offering the greatest propulsion efficiency. At ±30°, although the sailing distance was shortest, it enabled the fastest tacking, making it suitable for rapid directional changes. Performance at ±45° was comparatively less efficient overall. Additionally, the keel design effectively suppressed roll and yaw motions under strong wind conditions, further enhancing vessel stability. Compared to conventional soft sails, the rigid-wing sail maintained stable thrust even near the no-go zone, demonstrating superior aerodynamic performance and handling stability.
    In summary, this research successfully constructed a rigid-wing sailboat platform that integrates sensing, autonomous control, and navigational strategy. The implementation of a MIMO fuzzy controller enabled robust navigation and adaptive responsiveness in complex marine conditions. The results provide forward-looking value for Taiwan’s development of autonomous sailboats, green ocean technologies, and intelligent maritime systems, with potential applications in long-duration environmental monitoring, ocean observation, and low-carbon sailing missions.

    摘要 i Extended Abstract ii 目錄xi 表目錄 xiii 圖目錄 xiv 符號 xvii 第1章 緒論 1 1-1 研究背景 1 1-2 研究動機與目的 2 1-3 文獻回顧 3 1-4 論文架構 4 第2章 翼帆船設計與硬體架構 5 2-1 翼帆船設計 5 2-1-1 船體設計 6 2-1-2 翼帆設計 7 2-2 硬體配置 9 2-2-1 全球定位系統 9 2-2-2 陀螺儀 11 2-2-3 風速計 12 2-2-4 磁性編碼器 12 2-2-5 控制器配置 13 2-2-6 通訊配置 14 2-2-7 其他配置 14 第3章 帆船運動原理 17 3-1 帆船座標系 17 3-2 運動方程式 18 3-3 翼型升力 19 3-4 翼帆受力 22 3-5 帆船推力 23 3-6 翼帆尾翼操縱 24 3-7 航行操縱技術 25 第4章 模糊理論 28 4-1 模糊理論概述 28 4-2 模糊控制器 28 4-3 模糊化 29 4-3-1 模糊集合 30 4-3-2 歸屬函數 30 4-4 模糊推論 32 4-5 模糊資料規則庫 34 4-6 解模糊化 34 第5章 導航控制方法策略 37 5-1 航向推算法 37 5-2 模糊控制設計 37 5-2-1 航向誤差角及航線偏移量 38 5-2-2 多變數模糊航線控制器設計 41 5-3 迎風航行控制策略 46 5-3-1 翼帆控制策略 46 5-3-2 船速控制策略 47 5-3-3 導航控制策略 48 第6章 實驗結果與分析 50 6-1 無人船性能實驗 50 6-1-1 船速實驗 50 6-1-2 航向追蹤實驗 52 6-1-3 Pull-back test 55 6-1-4 Turning circle test 56 6-1-5 Zig-Zag test 60 6-1-6 路徑點追蹤實驗 64 6-2 風速與推力實驗 69 6-3 迎風航行實驗 71 6-3-1 翼帆帆船非典型性能表現 77 6-3-2 探討非典型原因 78 6-3-3 風速及風向對於帆船橫搖的影響 78 第7章 結論與未來展望 80 7-1 結論 80 7-2 未來展望 80 參考文獻 81

    Amini, H. M. Rad, and A. Fakhraee, "Comparison Final Velosity Between Sailing Boat With a Rigid Airfoil and Cloth Sail," in ASME International Mechanical Engineering Congress and Exposition, vol. 47705, pp. 691-701, 2006.
    Dhomé, U. "Further development and performance evaluation of the autonomous sailing boat Maribot Vane," ed, 2018.
    Dong, Y. N. Wu, J. Qi, X. Chen, and C. Hua, "Predictive course control and guidance of autonomous unmanned sailboat based on efficient sampled Gaussian process," Journal of Marine Science and Engineering, vol. 9, no. 12, p. 1420, 2021.
    Du, E. et al., "The role of concentrating solar power toward high renewable energy penetrated power systems," IEEE Transactions on Power Systems, vol. 33, no. 6, pp. 6630-6641, 2018.
    Hooda, D. and V. Raich, "Fuzzy Logic Models and Fuzzy Control," in An Introduction: Alpha Science International, p. 408, 2017.
    Huang, Z. L. Huang, K. Wang, R. Ma, H. Zhao, and Z. Wang, "Key Technology of Energy Efficiency Modeling and Optimization for Wing Sailboats," in 2021 6th International Conference on Transportation Information and Safety (ICTIS): IEEE, pp. 379-385, 2021.
    Manley, J.E. "Unmanned surface vehicles, 15 years of development," in OCEANS 2008: Ieee, pp. 1-4, 2008.
    Meinig, C. N. Lawrence-Slavas, R. Jenkins, and H.M. Tabisola, "The use of Saildrones to examine spring conditions in the Bering Sea: Vehicle specification and mission performance," in OCEANS 2015-MTS/IEEE Washington: IEEE, pp. 1-6, 2015.
    Petres, C. M.-A. Romero-Ramirez, F. Plumet, and B. Alessandrini, "Modeling and reactive navigation of an autonomous sailboat," in 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: IEEE, pp. 3571-3576, 2011.
    Plumet, F. C. Petres, M.-A. Romero-Ramirez, B. Gas, and S.-H. Ieng, "Toward an autonomous sailing boat," IEEE Journal of Oceanic Engineering, vol. 40, no. 2, pp. 397-407, 2014.
    Qin, H. Y. Wang, B. Qi, Y. Xue, X. Cao, and Z. Deng, "Optimization Strategies for Sail Angles of Unmanned Sailboats based on CFD and VPP," in OCEANS 2024-Singapore: IEEE, pp. 1-10, 2024.
    Silva, M.F. A. Friebe, B. Malheiro, P. Guedes, P. Ferreira, and M. Waller, "Rigid wing sailboats: A state of the art survey," Ocean Engineering, vol. 187, p. 106150, 2019.
    Smith, S. E. Witrant, and Y.-J. Pan, "High-Precision Heading Control of an Autonomous Sailboat: A Robust Nonlinear Approach," in OCEANS 2024-Halifax: IEEE, pp. 1-6, 2024.
    Stelzer, R. T. Proll, and R.I. John, "Fuzzy logic control system for autonomous sailboats," in 2007 IEEE International Fuzzy Systems Conference: IEEE, pp. 1-6, 2007.
    Tipsuwan, Y. P. Sanposh, and N. Techajaroonjit, "Overview and control strategies of autonomous sailboats—A survey," Ocean Engineering, vol. 281, p. 114879, 2023.
    Tretow, C. "Design of a free-rotating wing sail for an autonomous sailboat," ed, 2017.
    Zhang, R. et al., "A novel method of desynchronized operation of sails for ship wind-assisted propulsion system," Ocean Engineering, vol. 288, p. 115964, 2023.
    Zhou, L. K. Chen, Z. Chen, H. Dong, and D. Song, "Course control of unmanned sailboat based on BAS-PID algorithm," in 2020 International Conference on System Science and Engineering (ICSSE): IEEE, pp. 1-5, 2020.
    Zhu, H. H.-D. Yao, F. Thies, J.W. Ringsberg, and B. Ramne, "Propulsive performance of a rigid wingsail with crescent-shaped profiles," Ocean Engineering, vol. 285, p. 115349, 2023.
    吳晉源, "自主式水下載具X型舵操縱控制與性能分析," 碩士, 系統及船舶機電工程學系, 國立成功大學, 台南市, 2024.
    李家興, "自航帆船控制及導航系統之建構," 碩士, 機械與機電工程學系, 國立臺灣海洋大學, 基隆市, 2013.
    徐穎淳, "風帆輔助船舶航行之自動操控研究," 碩士, 系統及船舶機電工程學系, 國立成功大學, 台南市, 2014.
    張秉洋, "應用模糊理論於無人船之航線追蹤及操船控制研究," 碩士, 系統及船舶機電工程學系, 國立成功大學, 台南市, 2023.

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