一种自适应观测器设计和故障检测方法

利用模糊系统和径向高斯函数网络,设计一种具有自适应能力的模糊神经网络.用高斯函数表示模糊规则前件的隶属度函数,然后,构造一种递阶自组织在线学习算法,从输入输出样本数据中,通过学习提取模糊IF-THEN规则;在此基础上,提出一种非线性时变系统的自适应状态观测器设计和故障检测方法,并对其结构及特征进行了讨论,仿真结果表明,这种自适应状态观测器能很好地观测系统的状态,并能有效地应用于系统的故障检测.

Method of State Observer Design and Fault Detection

Radial Gaussian function networks based fuzzy systems with adaptive capability,are applied to the state estimation and fault detection of nonlinear time varying systems .In order to extract fuzzy IF THEN rules from input and output sample data through learning,the Gaussian function is employed to represent the membership functions of the premise part of fuzzy rules ,and then a hierarchically structural self organizing learning method is given.Based on this method of state estimation and fault detect for nonliear systems is proposed .The structure and characteristics of the observer are discussed. The results of simulation show that the proposed nonliear state observer can observe real system state and detect system fault satisfactorily.