A Novel Architecture for Civil Aviation Aircraft Intelligent Landing Using Dual Fuzzy Neural Network

Abstract:

This paper presents a novel architecture of intelligent landing control of an airplane using dual fuzzy neural networks, including roll control, pitch control and altitude hold control. The neural network control has been implemented in MATLAB and the data for training have been taken from Flight Gear Simulator. The flight performance has been shown in the Flight Gear Simulator. The objective is to improve the performance of conventional landing, roll, pitch and altitude hold controllers. Simulated results show that control for different flight phases is successful and the neural network controllers provide the robustness to system parameter variation.

• Periodical: Applied Mechanics and Materials (Volumes 313-314)
• Pages: 1385-1388
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.313-314.1385
• Online since: March 2013
• Authors: Kai Jun Xu
• Keywords: Civil Aviation Aircraft, Dual Fuzzy Neural Network, Flight Gear Simulator, Intelligent Landing System

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