摘要
利用模糊系统的径向高斯函数网络对一类非线性时变系统的状态进行了估计。给出了一种递阶自组织在线学习算法，提出了非线性时变系统的自适应状态观测器，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。
Radial Gaussian function networks based on fuzzy systems is applied to the state estimation of nonlinear time varying systems. A hierarchically structural self organizing learning method is given, and a state estimation method is proposed. The structure and characteristics of the observer are discussed. The results of estimation show that the proposed nonlinear state observer can observe real systems state satisfactorily.
出处
《航空学报》
EI
CAS
CSCD
北大核心
1998年第5期608-611,共4页
Acta Aeronautica et Astronautica Sinica
基金
博士后科学基金
关键词
状态估计
模糊神经网络
高斯函数
自适应状态
state estimation, fuzzy neural networks, Gaussian function, nonlinear system time dependence
