本文係以利用一套包含耐海性及操縱性的非線性六度運動數學模式並以四階Runge-Kutta之數值方法來求解計算船隻在波浪中的時程領域運動反應。由於船舶在海上航行時，受到外力時，橫搖是六度運動中最為棘手的部份。因此，在文中採用自調式類神經PID控制器來控制穩定翼，利用調整穩定翼的攻角以獲得所需之力與力矩來減低船舶在波浪中橫搖的情形。本研究分別在規則波、長峰波和短峰波中，將自調式類神經PID控制器與其他控制器做比較，發現本控制器有著與最佳化控制器幾乎相當的效率，但卻省去了基因演算法找尋最佳參數所消耗大量時間，並且廣泛的適應多種海況。因此本文所採用之減搖控制器對實際海況之減搖有相當的便利性與實用性。

The paper presents a mathematical model including seakeeping and maneuvering characteristics to analyze the ship roll reduction using the stabilizer fin in random waves. The self-tuning PID controller based on the neural network theory is applied to control the stabilizer fin which can optimally adjust the fin angle to reduce the ship roll motion in waves. Two multilayer neural networks are applied: (1) system identification for unknown systems (2) tuning system for PID gains determination. The present controller can automatically tune the optimal PID gains to reduce the ship roll motion in different sea states within a short period. The simulation results show the neural network based self-tuning PID control scheme developed here is indeed quite practical and successful for the ship roll reduction in the realistic sea.

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