Least-Squares-Based Iterative Identification Algorithm for Wiener Nonlinear Systems

被引：47
|
作者：
Zhou, Lincheng [1 ]
Li, Xiangli [1 ,2 ]
Pan, Feng [1 ]
机构：
[1] Jiangnan Univ, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China
[2] Jiangsu Coll Informat Technol, Wuxi 214153, Peoples R China
来源：
JOURNAL OF APPLIED MATHEMATICS | 2013年
基金：
中国国家自然科学基金;
关键词：
PARAMETER-ESTIMATION; HIERARCHICAL IDENTIFICATION; STOCHASTIC-SYSTEMS; CONVERGENCE;
D O I：
10.1155/2013/565841
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper focuses on the identification problem of Wiener nonlinear systems. The application of the key-term separation principle provides a simplified form of the estimated parameter model. To solve the identification problem of Wiener nonlinear systems with the unmeasurable variables in the information vector, the least-squares-based iterative algorithm is presented by replacing the unmeasurable variables in the information vector with their corresponding iterative estimates. The simulation results indicate that the proposed algorithm is effective.
引用
收藏
页数：6
相关论文
共 50 条
  • [1] Least-squares-based iterative identification algorithm for Hammerstein nonlinear systems with non-uniform sampling
    Li, Xiangli
    Ding, Ruifeng
    Zhou, Lincheng
    INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2013, 90 (07) : 1524 - 1534
  • [2] Least squares based and gradient based iterative identification for Wiener nonlinear systems
    Wang, Dongqing
    Ding, Feng
    SIGNAL PROCESSING, 2011, 91 (05) : 1182 - 1189
  • [3] On a least-squares-based algorithm for identification of stochastic linear systems
    Zheng, WX
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1998, 46 (06) : 1631 - 1638
  • [4] A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems
    Kazemi, Mandi
    Arefi, Mohammad Mehdi
    ISA TRANSACTIONS, 2017, 67 : 382 - 388
  • [5] Comments on "On a least-squares-based algorithm for identification of stochastic linear systems"
    Söderström, T
    Zheng, WX
    Stoica, P
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1999, 47 (05) : 1395 - 1396
  • [6] The recursive least squares identification algorithm for a class of Wiener nonlinear systems
    Ding, Feng
    Liu, Ximei
    Liu, Manman
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2016, 353 (07): : 1518 - 1526
  • [7] Least-squares-based iterative and gradient-based iterative estimation algorithms for bilinear systems
    Meihang Li
    Ximei Liu
    Feng Ding
    Nonlinear Dynamics, 2017, 89 : 197 - 211
  • [8] Least-squares-based iterative and gradient-based iterative estimation algorithms for bilinear systems
    Li, Meihang
    Liu, Ximei
    Ding, Feng
    NONLINEAR DYNAMICS, 2017, 89 (01) : 197 - 211
  • [9] Identification methods for Wiener nonlinear systems based on the least squares and gradient iterations
    Wang, Dongqing
    Chu, Yanyun
    Ding, Feng
    PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009), 2009, : 3632 - 3636
  • [10] Gradient-based and least-squares-based iterative algorithms for Hammerstein systems using the hierarchical identification principle
    Ding, Feng
    Liu, Xinggao
    Chu, Jian
    IET CONTROL THEORY AND APPLICATIONS, 2013, 7 (02): : 176 - 184
12345