Recursive maximum likelihood method for the identification of Hammerstein ARMAX system

Liang Ma; Xinggao Liu

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Recursive maximum likelihood method for the identification of Hammerstein ARMAX system

机译：Hammerstein ARMAX系统辨识的递推最大似然法

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摘要

Identification of Hammerstein nonlinear models has received much attention due to its ability to describe a wide variety of nonlinear systems. This paper considers the parameter estimation problem of ARMAX models for the Hammerstein systems. The recursive maximum likelihood method, which can be applied to online identification and occupies small memory capacity, is proposed to deal with the problem in here. It is an approximation of the maximum likelihood method. The parameters of the linear and nonlinear parts of the Hammerstein model and the noise model can be directly obtained without using the overparameterization technique. Finally, the proposed method is applied to a classic Hammerstein ARMAX system and is compared with RLS method in detail. The research results show the effectiveness of the proposed method.

机译：Hammerstein非线性模型的识别由于能够描述各种各样的非线性系统而备受关注。本文考虑了Hammerstein系统的ARMAX模型的参数估计问题。在此提出了一种递归最大似然方法，该方法可以应用于在线识别，并且占用较小的存储容量。它是最大似然法的近似值。 Hammerstein模型和噪声模型的线性和非线性部分的参数可以直接获得，而无需使用超参数化技术。最后，将该方法应用于经典的Hammerstein ARMAX系统，并与RLS方法进行了比较。研究结果表明了该方法的有效性。

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来源
《Applied Mathematical Modelling》 |2016年第14期|6523-6535|共13页
作者
Liang Ma; Xinggao Liu;
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作者单位

State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, PR China;

State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, PR China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Recursive identification; RML; Hammerstein ARMAX system;

机译：递归识别;RML;Hammerstein ARMAX系统;

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专利

1. A nonlinear recursive instrumental variables identification method of Hammerstein ARMAX system [J] . Ma Liang, Liu Xinggao Nonlinear dynamics . 2015,第2期

机译：Hammerstein ARMAX系统的非线性递归工具变量辨识方法。
2. A novel APSO-aided maximum likelihood identification method for Hammerstein systems [J] . Sun J., Liu X. Nonlinear dynamics . 2013,第1a2期

机译：Hammerstein系统的一种新型的APSO辅助最大似然识别方法
3. Maximum likelihood Newton recursive and the Newton iterative estimation algorithms for Hammerstein CARAR systems [J] . Junhong Li, Feng Ding, Liang Hua Nonlinear dynamics . 2014,第1a2期

机译：Hammerstein CARAR系统的最大似然牛顿递归和牛顿迭代估计算法
4. Parameter identification for Hammerstein nonlinear systems using the maximum likelihood principle and Levenberg-Marquardt optimization method [C] . Junhong Li, Weixing Zheng, Juping Gu, Chinese Control Conference . 2016

机译：基于最大似然原理和Levenberg-Marquardt优化方法的Hammerstein非线性系统参数识别
5. An adaptive Kalman filter design using recursive maximum likelihood identification. [D] . Kelly, Donald Andrew. 1990

机译：使用递归最大似然识别的自适应卡尔曼滤波器设计。
6. SCUMBLE: a method for systematic and accurate detection of codon usage bias by maximum likelihood estimation [O] . Morten Kloster, Chao Tang 2008

机译：SCUMBLE：一种通过最大似然估计来系统准确地检测密码子使用偏倚的方法
7. Blind Maximum Likelihood Identification of Hammerstein Systems [O] . L. Vanbeylen, R. Pintelon, J. Schoukens 2014

机译：Hammerstein系统的盲极大似然识别

Recursive maximum likelihood method for the identification of Hammerstein ARMAX system

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