Initial Estimates for Wiener-Hammerstein Models using the Best Linear Approximation

被引：6
|
作者：
Lauwers, Lieve [1 ]
Schoukens, Johan [1 ]
Pintelon, Rik [1 ]
机构：
[1] Vrije Univ Brussels, Dept ELEC, B-1050 Brussels, Belgium
来源：
2008 IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1-5 | 2008年
关键词：
Wiener-Hammerstein systems; initial estimates; best linear approximation;
D O I：
10.1109/IMTC.2008.4547169
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper a method is proposed to initialize the linear dynamic blocks of a Wiener-Hammerstein model. The idea is to build these blocks from the poles and the zeros of the Best Linear Approximation of the system under test, which can easily be extracted from the data. This approach results in an easy to solve problem (linear-in-the-parameters) from which initial estimates for the linear dynamics can be obtained The proposed method is applied to simulation data from a Wiener-Hammerstein system.
引用
收藏
页码：928 / 932
页数：5
相关论文
共 50 条
  • [41] Identification of a Wiener-Hammerstein system using an incremental nonlinear optimisation technique
    Tan, Ai Hui
    Wong, Hin Kwan
    Godfrey, Keith
    CONTROL ENGINEERING PRACTICE, 2012, 20 (11) : 1140 - 1148
  • [42] A recursive hierarchical parametric estimation algorithm for nonlinear systems described by Wiener-Hammerstein models
    Ghanmi, Afef
    Elloumi, Mourad
    Salhi, Houda
    Kamoun, Samira
    ASIAN JOURNAL OF CONTROL, 2020, 22 (03) : 1065 - 1074
  • [43] Identification of Wiener-Hammerstein models based on variational bayesian approach in the presence of process noise
    Liu, Qie
    Tang, Xinming
    Li, Junhao
    Zeng, Jianxue
    Zhang, Ke
    Chai, Yi
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2021, 358 (10): : 5623 - 5638
  • [44] Synthesis of nonlinear dynamic Wiener-Hammerstein models by input-output memory redistribution
    Avt Telemekh, 11 (21-32):
  • [45] Identification of a Wiener-Hammerstein system using the polynomial nonlinear state space approach
    Paduart, J.
    Lauwers, L.
    Pintelon, R.
    Schoukens, J.
    CONTROL ENGINEERING PRACTICE, 2012, 20 (11) : 1133 - 1139
  • [46] Separation identification of a neural fuzzy Wiener-Hammerstein system using hybrid signals
    Li, Feng
    Yang, Hao
    Cao, Qingfeng
    FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, 2024, 25 (06) : 856 - 868
  • [47] Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels
    Dreesen, Philippe
    Westwick, David T.
    Schoukens, Johan
    Ishteva, Mariya
    LATENT VARIABLE ANALYSIS AND SIGNAL SEPARATION (LVA/ICA 2017), 2017, 10169 : 16 - 25
  • [48] Tensor Factorization based Estimates of Parallel Wiener Hammerstein Models
    Westwick, David T.
    Ishteva, Mariya
    Dreesen, Philippe
    Schoukens, Johan
    IFAC PAPERSONLINE, 2017, 50 (01): : 9468 - 9473
  • [49] Measuring the Best Linear Approximation of Wiener Systems Using Multilevel Sequences
    De Angelis, A.
    Schoukens, J.
    Godfrey, K. R.
    Carbone, P.
    2017 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC), 2017, : 1077 - 1081
  • [50] Black box model identification of nonlinear input-output models: A Wiener-Hammerstein benchmark
    Piroddi, Luigi
    Farina, Marcello
    Lovera, Marco
    CONTROL ENGINEERING PRACTICE, 2012, 20 (11) : 1109 - 1118
12345