水下載具之模糊類神經網路控制

Fuzzy Neural Network Control for Underwater Vehicles

廖偉盛(Wei-Sheng Liao)

指導教授 ： 黃英哲

元智大學/電機通訊學院/電機工程學系/碩士(2009年)

摘要

本論文提出一應用於自主式水下載具的模糊類神經網路控制器，採用倒傳遞演算法調整類神經網路中的權重值、中心值、變異數以達成目標之追蹤控制。採用倒傳遞演算法可減少程式的運算量，亦可增加水下載具的反應速度。然而，所提出的模糊類神經網路控制不僅能追蹤弦波訊號更能直接做為控制器，控制水下載具追蹤平擺角之目標值。數值模擬結果顯示此模糊類神經網路控制器不需要太大的控制力就能有很好的追蹤效果。最後，為了控制一個兼具體積小與靈活性高的水下載具，能行駛於狹隘且惡劣的環境，提出一模糊類神經網路控制器，使得水下載具具備追蹤與定位的功能，同時驗證本文所提出之模糊類神經網路控制器是有效的。

關鍵字

水下載具 ； 類神經網路 ； 模糊類神經網路 ； 倒傳遞 ； 自主式

並列摘要

This thesis proposes a fuzzy neural network (FNN) controller for autonomous underwater vehicles (AUVs). In order to track signals or specific desired yaw angle, backpropagation algorithm is presented to tune the weights, means, and variances in the fuzzy neural network. Backpropagation algorithm can reduce the program operation time and increases the reaction speed. The simulation results illustrate that the proposed controller has good tracking performance without large control efforts. Finally, this method is applied to control a small autonomous underwater vehicle which travels in a narrow and harsh environment. The proposed fuzzy neural network controller lets the autonomous underwater vehicle have the functions of tracking and positioning. The simulation results verify that the proposed fuzzy neural network controller is effective.

並列關鍵字

underwater vehicles ； neural network ； fuzzy neural network ； backpropagation ； autonomous

參考文獻

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