基于模糊基函数网络的系统故障检测

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.最后给出了某飞机的微波着陆系统故障信息检测仿真实例.

Fuzzy basis function network based approach for fault information detection in unknown systems

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.