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頁籤選單縮合
題 名 | 類神經模糊自航器之設計及應用=On the Design and Application of Neural-Fuzzy Autopilot |
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作 者 | 何曙光; 曾慶耀; | 書刊名 | 中國造船暨輪機工程學刊 |
卷 期 | 16:1 1997.02[民86.02] |
頁 次 | 頁69-83 |
分類號 | 444.6 |
關鍵詞 | 自航器; 類神經模糊邏輯控制器; 倒傳遞; 中間目標控制器; Autopilot; Neural-fuzzy controller; Back-propagation; Interim target controller; |
語 文 | 中文(Chinese) |
中文摘要 | 由於船舶運動特性相當複雜,無法以理論數學模式完全界定之,因此仰賴一明確數學模式之傳統式控制器設計方式在自航器之應用受到相當限制。然而領港人員卻往往憑藉其累積之領航經驗即可充分的操縱船舶行為。同時模糊集合理論之邏輯法則,正可表達人為領航模式,因此可預期模糊自航器若設計得當,將具有與人為領航模式接近之成效。由於模糊邏輯控制對環境變化產生之影響無法回授至控制器本身,因此缺乏適應性能力。故本文將之結合類神經網路與中間目標控制器,形成線上訓練類神經模糊控制架構,使用倒傳遞演算法隨時由誤差量修正控制規則庫之歸函數,以達適應性控制之需求。 |
英文摘要 | As the mechanism involved in ship maneuvering is highly involved, characterization of ship behavior by a pure mathematical model would be very difficult if not impossible. Hence, mathematical model-based autopilot design method is of limited applicability in this case. However, human pilots, who probably know little about the mathematical model of a ship, are able to control a ship satisfactorily based on their experience. Fuzzy logic rules are capable of describing the human piloting process; hence, a properly designed fuzzy autopilot is expected to be as good as a skilled human pilot. However, a fuzzy logic controller can't adapt to the changing environments, it can't maintain optimal performance under various operating conditions. By in corporation of neural network and interim target controller into the fuzzy autopilot, an on-line trained neura-fuzzy autopilot is developed. Specifically, the mambership function used in defining the fuzy logic rule base is adjusted by minimizing a performance index with back-propagation algorithm, consequently this makes the neural fuzzy autopilot capable of adapting itself to varying working condition. |
本系統中英文摘要資訊取自各篇刊載內容。