摘要
给出了基于T S模型的模糊基函数网络 (FBFN) ,并提出了一种基于FBFN的未知系统故障信息检测通用方法 .将未知系统分为已知部分和未知部分 .系统的实际输出包括已知部分输出、未知部分输出和故障信息等三部分 .已知部分用数学模型描述 .未知部分包括系统的建模误差、噪声干扰等不确定性 ,用FBFN逼近 .因此 ,根据系统的实际输出、数学模型输出和FBFN输出可估计出故障信息 .
Fuzzy basis function network (FBFN) based on T S fuzzy model is given. A general approach for fault information detection in unknown systems using FBFN is present. The unknown system is composed of known part and unknown part. The output of an actual system is composed of three portions: the output of a mathematical model, the output of unknown part and fault information. The known part can be represented by a mathematical model. The unknown part, which includes the uncertainty of model error, disturbance inputs, etc, is estimated by a FBFN. The fault information in the unknown system can be estimated using the outputs of actual system, the mathematical model and FBFN.A simulation example of fault information detection in a microwave landing system of an aircraft is given.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2003年第7期570-574,共5页
Journal of Beijing University of Aeronautics and Astronautics
基金
国家自然科学基金重点资助项目 ( 60 2 3 40 10 )
关键词
故障检测
模糊逻辑
神经网络
未知系统
微波着陆系统
fault detection
fuzzy logic
neural networks
unknown system
microwave landing system