Hierarchical recursive least squares algorithms for Hammerstein nonlinear autoregressive output-error systems

被引：83

作者：

Kang, Zhen ^{[1
]}

Ji, Yan ^{[1
]}

Liu, Ximei ^{[1
]}

机构：

[1] Qingdao Univ Sci & Technol, Coll Automat & Elect Engn, Qingdao 266061, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING | 2021年 / 35卷 / 11期

基金：

中国国家自然科学基金;

关键词：

hierarchical identification principle; least squares; nonlinear system; parameter estimation; recursive identification; PARAMETER-ESTIMATION; IDENTIFICATION METHOD; COLLISION-AVOIDANCE; BILINEAR-SYSTEMS; TRACKING CONTROL; FAULT-DIAGNOSIS; STATE; MATRIX;

D O I：

10.1002/acs.3320

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 article considers the parameter estimation problem of Hammerstein nonlinear autoregressive output-error systems with autoregressive moving average noises. Applying the key term separation technique, the original system is decomposed into three subsystems: the first subsystem contains the unknown parameters related to the output, the second subsystem contains the unknown parameters related to the input, and the third subsystem contains the unknown parameters related to the noise model. A hierarchical recursive least squares algorithm is proposed based on the hierarchical identification principle for interactively identifying each subsystem. The simulation results confirm that the proposed algorithm is effective in estimating the parameters of Hammerstein nonlinear autoregressive output-error systems.

引用

页码：2276 / 2295

页数：20

共 50 条

[1] Recursive and Iterative Least Squares Parameter Estimation Algorithms for Multiple-Input–Output-Error Systems with Autoregressive Noise
Jiling Ding
[J]. Circuits, Systems, and Signal Processing, 2018, 37 : 1884 - 1906
[2] Hierarchical Least Squares Identification for Hammerstein Nonlinear Controlled Autoregressive Systems
Huibo Chen
Feng Ding
[J]. Circuits, Systems, and Signal Processing, 2015, 34 : 61 - 75
[3] Hierarchical Least Squares Identification for Hammerstein Nonlinear Controlled Autoregressive Systems
Chen, Huibo
Ding, Feng
[J]. CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2015, 34 (01) : 61 - 75
[4] Filtering Based Multi-Stage Recursive Least Squares Parameter Estimation Algorithm for Input Nonlinear Output-Error Autoregressive Systems
Ma Junxia
Chen Jing
Ding Feng
[J]. PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 1921 - 1925
[5] Maximum likelihood interval-varying recursive least squares identification for output-error autoregressive systems with scarce measurements
Li, Shutong
Ji, Yan
[J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2023, 360 (11): : 7230 - 7246
[6] Auxiliary model-based recursive least squares and stochastic gradient algorithms and convergence analysis for feedback nonlinear output-error systems
Miao, Guangqin
Yang, Dan
Ding, Feng
[J]. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2024,
[7] Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems
Guo, Yunze
Wan, Lijuan
Xu, Ling
Ding, Feng
Alsaedi, Ahmed
Hayat, Tasawar
[J]. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2019, 17 (06) : 1547 - 1557
[8] Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems
Yunze Guo
Lijuan Wan
Ling Xu
Feng Ding
Ahmed Alsaedi
Tasawar Hayat
[J]. International Journal of Control, Automation and Systems, 2019, 17 : 1547 - 1557
[9] Decomposition based recursive least squares parameter estimation for Hammerstein nonlinear controlled autoregressive systems
Chen, Huibo
Ding, Feng
[J]. 2013 AMERICAN CONTROL CONFERENCE (ACC), 2013, : 2436 - 2441
[10] Auxiliary model-based least-squares identification methods for Hammerstein output-error systems
Ding, Feng
Shi, Yang
Chen, Tongwen
[J]. SYSTEMS & CONTROL LETTERS, 2007, 56 (05) : 373 - 380

← 1 2 3 4 5 →