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Title: Ship Steering Autopilot Based on ANFIS Framework and Conditional Tuning Scheme
Authors: Sin-Der Lee;Ching-Yaw Tzeng;Wen-Wei Huang
Contributors: 國立臺灣海洋大學:運輸科學系
Date: 2013
Issue Date: 2016-08-23T02:40:39Z
Publisher: Marine Engineering Frontiers
Abstract: Abstract: The ever changing sea condition makes it difficult to use a single mathematical model to describe the nonlinear dynamic behavior of a vessel. Hence, the performance of model-based autopilots is generally inferior to that of modelfree designs such as fuzzy controllers or neural networks. This study combines the robustness property of fuzzy logic controllers and the learning capability of artificial neural networks to create an ANFIS (Adaptive Network-based Fuzzy Inference System) ship steering autopilot. In addition, a conditional tuning scheme is presented to increase the response speed of the proposed autopilot, while simultaneously reducing the overshoot. The performance of the proposed autopilot is evaluated by performing a series of course-changing and track-keeping simulations. The simulation results show that the proposed autopilot provides a more adaptive and robust control performance than a traditional PD fuzzy controller under typical sea conditions.
Relation: 1(3)
Appears in Collections:[Department of Transportation Science] Periodical Articles

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