摘要
最小二乘法可用于动态系统、静态系统、线性系统和非线性系统的参数估计,可用于离线估计,也可用于在线估计;文章在增广最小二乘递推算法的基础上引入限定记忆方式,获得了增广最小二乘限定记忆参数估计递推算法(RFMELS),解决了增广最小二乘递推算法的数据饱和问题,仿真结果表明了RFMELS算法的有效性。
The least squares method is used for parameter identification of dynamic, static, linear or nonlinear systems. This paper combines the recursive extended least squares method with fixed memory length, thus obtaining the recursive fixed memory extended least squares（RFMELS） method. The new method resolves the problem of data saturation. Simulation results indicate the validity of the RFMELS method.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2009年第7期977-980,共4页
Journal of Hefei University of Technology：Natural Science
关键词
增广最小二乘
限定记忆
参数辨识
递推算法
SIMULINK仿真
extended least squares method
fixed memory
parameter identification
recursive algorithrn
Simulink simulation
