Partially coupled gradient-based iterative identification methods for multivariable output-error moving average systems

被引：7
作者：
Wang, Feifei [1 ]
Ding, Feng [1 ]
机构：
[1] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China
来源：
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL | 2016年 / 26卷 / 04期
基金：
中国国家自然科学基金;
关键词：
parameter estimation; iterative identification; hierarchical identification principle; coupling identification concept; multivariable system;
D O I：
10.1504/IJMIC.2016.081139
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper focuses on the identification problems of multivariable output-error moving average systems and develops a partially coupled gradient-based iterative algorithm to estimate the parameters of the systems. The key is combining the hierarchical identification principle and the coupling identification concept to decompose a multivariable system into m subsystems (m is the number of outputs), and then to identify the subsystems one by one. Compared with the gradient-based iterative algorithm, the partially coupled gradient-based iterative algorithm requires less computational efforts. The simulation results show that the proposed algorithms are effective.
引用
收藏
页码：293 / 302
页数：10
相关论文
共 50 条
  • [21] Hierarchical least-squares based iterative identification for multivariable systems with moving average noises
    Han, Heqiang
    Xie, Li
    Ding, Feng
    Liu, Xinggao
    MATHEMATICAL AND COMPUTER MODELLING, 2010, 51 (9-10) : 1213 - 1220
  • [22] Partially coupled gradient estimation algorithm for multivariable equation-error autoregressive moving average systems using the data filtering technique
    Liu, Qinyao
    Ding, Feng
    Xu, Ling
    Yang, Erfu
    IET CONTROL THEORY AND APPLICATIONS, 2019, 13 (05) : 642 - 650
  • [23] Newton iterative identification for a class of output nonlinear systems with moving average noises
    Ding, Feng
    Ma, Junxia
    Xiao, Yongsong
    NONLINEAR DYNAMICS, 2013, 74 (1-2) : 21 - 30
  • [24] Gradient-based iterative parameter estimation for output error autoregressive systems using hierarchical principle
    Sha, Liangbin
    Ji, Yan
    PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, : 1684 - 1689
  • [25] Newton iterative identification for a class of output nonlinear systems with moving average noises
    Feng Ding
    Junxia Ma
    Yongsong Xiao
    Nonlinear Dynamics, 2013, 74 : 21 - 30
  • [26] Partially-coupled least squares based iterative parameter estimation for multi-variable output-error-like autoregressive moving average systems
    Ma, Hao
    Pan, Jian
    Ding, Feng
    Xu, Ling
    Ding, Wenfang
    IET CONTROL THEORY AND APPLICATIONS, 2019, 13 (18) : 3040 - 3051
  • [27] Auxiliary model-based least-squares identification methods for Hammerstein output-error systems
    Ding, Feng
    Shi, Yang
    Chen, Tongwen
    SYSTEMS & CONTROL LETTERS, 2007, 56 (05) : 373 - 380
  • [28] Hierarchical gradient-based identification of multivariable discrete-time systems
    Ding, F
    Chen, TW
    AUTOMATICA, 2005, 41 (02) : 315 - 325
  • [29] Model transformation based distributed stochastic gradient algorithm for multivariate output-error systems
    Liu, Qinyao
    Chen, Feiyan
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2023, 54 (07) : 1484 - 1502
  • [30] Multi-innovation gradient-based iterative identification methods for feedback nonlinear systems by using the decomposition technique
    Yang, Dan
    Ding, Feng
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2023, 33 (13) : 7755 - 7773
12345