Intelligent Landing Control System for Civil Aviation Aircraft with Dual Fuzzy Neural Network
This paper presents the intelligent landing control system that overcome wind disturbance problem of a civil aviation aircraft during the landing phase when subjected to severe winds and failures such as stuck control surfaces. The controller architecture uses a dual fuzzy neural network (DFNN) controller, which is capable of implementing fuzzy inference in general and neural network mechanism in particular. A systematic method for mapping an existing rule base into a set of dual fuzzy neural network weights has also been presented. However, in order to utilize this method to initialize the dual fuzzy neural network weights, such a rule base obtained from domain experts or from experimental data through systematic, knowledge acquisition methods has been proposed. It uses one neural network as on-line learning and does not need a priori training. Simulations show that it improved the performance of conventional automatic landing system (ALS) and guide the aircraft to a safe landing.
Intelligent landing control system dual fuzzy neural network civil aviation craft learning algorithm
Kaijun Xu Guangming Zhang Yang Xu
Department of air navigation, School of flight technology Civil aviation flight university of China Department of air navigation, School of flight technology Civil aviation flight university of China Intelligent Control and Development Center Southwest Jiaotong University Chengdu, Sichuan 610031, P.
国际会议
上海
英文
170-174
2011-07-26（万方平台首次上网日期，不代表论文的发表时间）