A Dual Fuzzy Neuro Controller using Genetic Algorithm in Civil Aviation Intelligent Landing System

摘要：

A kind of dual fuzzy neuro control algorithm (DFNC) for civil aviation aircraft intellegent landing system is developed in this paper. The DFNC algorithm uses Genetic Algorithm (GA) as the optimization technique and chooses best control performance of approaching and landing to be the optimization object. Real-time recurrent learning (RTRL) is applied to train the RNN that uses gradient-descent of the error function with respect to the weights to perform the weights updates. Convergence analysis of system error is provided. The control scheme utilizes five crossover methods of Gas to search optimal control parameters. Simulations show that the proposed intelligent controller has better performance than the conventional controller.

关键词： intelligent landing system dual fuzzy neuro controller genetic algorithm civil aviation

作者: Kaijun Xu Guangming Zhang Yang Xu

作者单位: 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,

会议类型: 国际会议

会议名称: 4th International Conference on Measuring Technology and Mechatronics Automation(第四届检测技术与机电自动化国际会议 ICMTMA 2012)

会议地点: 三亚

会议语种:英文

页码: 11-14

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）