| 增广最小二乘限定记忆参数估计算法与仿真 |
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| 引用本文： | 鲁照权,胡金东,胡焱东,俞宗嘉.增广最小二乘限定记忆参数估计算法与仿真[J].合肥工业大学学报(自然科学版),2009,32(7). |
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| 作者姓名： | 鲁照权 胡金东 胡焱东 俞宗嘉 |
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| 作者单位： | 合肥工业大学,电气与自动化工程学院,安徽,合肥,230009 |
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| 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.
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| 关 键 词： | 增广最小二乘 限定记忆 参数辨识 递推算法 Simulink仿真 |
Recursive fixed memory extended least squares method and simulation research |
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| LU Zhao-quan,HU Jin-dong,HU Yan-dong,YU Zong-jia.Recursive fixed memory extended least squares method and simulation research[J].Journal of Hefei University of Technology(Natural Science),2009,32(7). |
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| Authors: | LU Zhao-quan HU Jin-dong HU Yan-dong YU Zong-jia |
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| Abstract: | 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. |
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| Keywords: | extended least squares method fixed memory parameter identification recursive algorithm Simulink simulation |
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