On the Study of Fuzzy and Artificial Neural Network Ship Steering Autopilots
| Autor: | Wen-Wei Huang, 黃文煒 |
|---|---|
| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 The ever changing sea condition makes it difficult to use a single mathematical model in describing the dynamic behavior of a ship. Hence, the performance of traditional model-based autopilot is limited due to the so called model uncertainty. On the contrary, the fuzzy logic and artificial neural network controller design methods do not require explicit modeling of the plant to be controlled; hence, better robustness and adaptive capabilitiy can be expected. This work aims at combining the robustness property associated a fuzzy logic controller and the learning capability of an artificial neural network. An ANFIS(Adaptive Network_based Fuzzy Inference System) framework has been proposed that significantly reduces the efforts required in the selection of appropriate membership functions through proper learning process. Specifically, a function_based tuning method and a direct neural network have been employed to increase the response speed, while reducing the amount of overshoot. The Matlab/Simulink and related toolboxes are used in the simulation experiments and the line of sight guidance method has been adopted in computing the reference heading needed in the track-keeping mission. A series of course-changing and track-keeping simulations has been conducted to demonstrate the advantage of the proposed ANFIS design framework over the traditional internal model control (IMC), fuzzy, and neural network design methods. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|