船舶 接離岸의 퍼지學習制御 = On the Ship's Berthing Control by introducing the Fuzzy Neural Network

다국어 초록 (Multilingual Abstract)

Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model, but the results of such studies have not reached to our satisfactory level due to its non-liner characteristics at low speed. In this paper, the authors propose a new berthing control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS-90 MK Ⅲ) and represent the ship motion characteristics internally. According to learning procedure, both FNN controllers can tune membership functions and identify fuzzy control rules automatically. The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.

목차 (Table of Contents)

• Abstract
• 1. 序 論
• 2. 퍼지 神經回路網
• 3. 接離岸 System의 構成과 航行制御 Subsystem
• 4. 接岸停船制御 Subsystem의 表現과 學習데이타의 獲得
• 5. 接岸停船制御 Subsystem의 前件部 所屬函數 및 制御規則의 同定
• 6. 結 論
• 參考文獻