Auxiliary model-based hierarchical stochastic gradient methods for multiple-input multiple-output systems DOI

Haoming Xing,

Feng Ding, Feng Pan

и другие.

Journal of Computational and Applied Mathematics, Год журнала: 2023, Номер 442, С. 115687 - 115687

Опубликована: Ноя. 22, 2023

Язык: Английский

Recursive identification methods for general stochastic systems with colored noises by using the hierarchical identification principle and the filtering identification idea DOI
Feng Ding, Ling Xu, Xiao Zhang

и другие.

Annual Reviews in Control, Год журнала: 2024, Номер 57, С. 100942 - 100942

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

74

Filtered generalized iterative parameter identification for equation‐error autoregressive models based on the filtering identification idea DOI
Feng Ding, Xingling Shao, Ling Xu

и другие.

International Journal of Adaptive Control and Signal Processing, Год журнала: 2024, Номер 38(4), С. 1363 - 1385

Опубликована: Янв. 28, 2024

Summary By using the collected batch data and iterative search, based on filtering identification idea, this article investigates proposes a filtered multi‐innovation generalized projection‐based method, gradient‐based least squares‐based method for equation‐error autoregressive systems described by models. These methods can be extended to other linear nonlinear scalar multivariable stochastic with colored noises.

Язык: Английский

Процитировано

67

Novel parameter estimation method for the systems with colored noises by using the filtering identification idea DOI
Ling Xu, Feng Ding, Xiao Zhang

и другие.

Systems & Control Letters, Год журнала: 2024, Номер 186, С. 105774 - 105774

Опубликована: Март 14, 2024

Язык: Английский

Процитировано

60

Adaptive Multi-Innovation Gradient Identification Algorithms for a Controlled Autoregressive Autoregressive Moving Average Model DOI
Ling Xu, Huan Xu, Feng Ding

и другие.

Circuits Systems and Signal Processing, Год журнала: 2024, Номер 43(6), С. 3718 - 3747

Опубликована: Март 13, 2024

Язык: Английский

Процитировано

56

Joint iterative state and parameter estimation for bilinear systems with autoregressive noises via the data filtering DOI
Siyu Liu, Yanjiao Wang, Feng Ding

и другие.

ISA Transactions, Год журнала: 2024, Номер 147, С. 337 - 349

Опубликована: Фев. 3, 2024

Язык: Английский

Процитировано

53

Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises DOI

Haoming Xing,

Feng Ding, Xiao Zhang

и другие.

Systems & Control Letters, Год журнала: 2024, Номер 186, С. 105762 - 105762

Опубликована: Март 14, 2024

Язык: Английский

Процитировано

51

A novel recursive multivariate nonlinear time-series modeling method by using the coupling identification concept DOI
Yihong Zhou, Feng Ding

Applied Mathematical Modelling, Год журнала: 2023, Номер 127, С. 571 - 587

Опубликована: Дек. 7, 2023

Язык: Английский

Процитировано

50

Online identification methods for a class of Hammerstein nonlinear systems using the adaptive particle filtering DOI
Huan Xu, Ling Xu, Shaobo Shen

и другие.

Chaos Solitons & Fractals, Год журнала: 2024, Номер 186, С. 115181 - 115181

Опубликована: Июль 1, 2024

Язык: Английский

Процитировано

35

Online identification of Hammerstein systems with B‐spline networks DOI
Yanjiao Wang, Yiting Liu, Jiehao Chen

и другие.

International Journal of Adaptive Control and Signal Processing, Год журнала: 2024, Номер 38(6), С. 2074 - 2092

Опубликована: Март 27, 2024

Summary Nonlinear systems widely exist in real‐word applications and the research for these has enjoyed a long fruitful history, including system identification community. However, modeling nonlinear is often quite challenging still remains many unresolved questions. This article considers online issue of Hammerstein systems, whose static function modeled by B‐spline network. First, model studied constructed using bilinear parameter decomposition model. Second, recursive algorithms are proposed to find estimates moving data window particle swarm optimization procedure, show that converge their true values with low computational burden. Numerical examples also given test effectiveness algorithms.

Язык: Английский

Процитировано

25

Parameter Estimation and Model-free Multi-innovation Adaptive Control Algorithms DOI
Xin Liu,

Pinle Qin

International Journal of Control Automation and Systems, Год журнала: 2024, Номер 22(11), С. 3509 - 3524

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

21