臺灣博碩士論文加值系統

近年來模糊理論與類神經理論已在廣泛的應用在各個領域中，本文利用類神經的自我學習能力，應用倒傳遞類神經網路，結合模糊的架構，來設計一個類神經-模糊的避碰系統。應用類神經的自我學習模式，調整模糊控制中的歸屬函數之中心點及寬度，以期避碰系統可以更迅速地將所建議之船艏角傳達給自動操舵系統，而達到避碰效果。
由於 控制理論具備排除系統不確定性及干擾的優越能力，本文設計一個類神經- 的自動操舵系統，即於在 控制系統中，加入類神經之自動學習功能，以加速 觀測器之收歛速度，使自動操舵系統，可以更有效的追蹤避碰系統所建議之船的航向角度。本研究把類神經-模糊的避碰系統與類神經- 的自動操舵系統做整合，形成完善的避碰理論，最後再以各種避碰遭遇狀況做電腦模擬，分別以障礙物避碰及船舶避碰做模擬，以驗證本文理論的可行性。

Abstract
Experts’ experiences and International Collision Avoidance Rules are two of the urgent information required in designing the ship collision-avoidance systems and both of them are in the linguistic form. Since the fuzzy system can provide a linguistic framework for handling system uncertainties, a fuzzy-based collision-avoidance system is studied in this paper. To select the number of inference rules and the input-output membership functions in a fuzzy system more efficiently, a systematic fuzzy collision-avoidance system is proposed in this study. To perform the ship task of collision-avoidance effectively, a robust autopilot based on H∞-control methodology and neural strategy is designed to form the proposed neural-H∞autopilot system. The neural-network learning algorithm used in this study is able to increase the speed in finding the H∞-optimal controller of the autopilot. Computer simulation results of a ship model reveal that the proposed neural-fuzzy collision-avoidance system works well when the suggested collision-avoidance route is executed by the designed neural-H∞autopilot system.

目 錄
AbstractI
摘要II
誌謝III
目錄IV
圖目錄VI
第一章 緒論1
1-1 研究動機1
1-2 文獻回顧2
1-3 論文架構3
第二章 船舶避碰與安全領域4
2-1 船舶安全領域4
2-2 船舶避碰措施7
第三章 類神經-模糊避碰系統之設計13
3-1~1 類神經網路13
3-1~2 類神經網路之運作15
3-1~3 倒傳遞網路的學習法則16
3-2~1 模糊理論概念19
3-2~2 模糊控制器架構20
3-2~3 模糊控制器運算過程23
3-3 類神經-模糊避碰系統之設計26
3-4 類神經-模糊避碰系統之過程33
第四章 類神經- 操舵系統之設計42
4-1~1 理論42
4-1~2 範數（norm）42
4-2 擴增系統矩陣45
4-3 控制問題的求解49
4-4 類神經- 自動操舵系統之設計53
第五章 電腦模擬57
5-1 模擬結果59
第六章 結論與未來展望71
參考文獻72
附錄76

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