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[期刊论文]

Two-stage extended recursive gradient algorithm for locally linear RBF-based autoregressive models with colored noises

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author:

Zhou, Yihong (Zhou, Yihong.) [1] | Ding, Feng (Ding, Feng.) [2] | Yang, Erfu (Yang, Erfu.) [3]

Indexed by:

EI

Abstract:

A novel parameter identification method for locally linear radial basis function-based autoregressive models in presence of colored noises is proposed in this paper. Taking advantage of the global nonlinear and local linear structural characteristics of the models, two dynamical criterion functions are constructed based on the separated parameters to realize the dynamical acquisition and utilization of the entire process data. Two recursive gradient sub-algorithms are derived for estimating the separated parameters by using the nonlinear gradient optimization. To coordinate the associated variables existing in the sub-algorithms and to estimate the unmeasurable noise terms, we combine the sub-algorithms and propose a two-stage extended recursive gradient (2S-ERG) algorithm. In addition, an extended recursive gradient algorithm is given as a comparison. The feasibility of the 2S-ERG algorithm is validated by numerical simulations. © 2022 ISA

Keyword:

Parameter estimation Radial basis function networks White noise

Community:

  • [ 1 ] [Zhou, Yihong]Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi; 214122, China
  • [ 2 ] [Ding, Feng]Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi; 214122, China
  • [ 3 ] [Ding, Feng]College of Mathematics and Computer Science, Fuzhou University, Fuzhou; 350116, China
  • [ 4 ] [Yang, Erfu]Department of Design, Manufacturing and Engineering Management, University of Strathclyde, Glasgow, G1 1XJ, Scotland, United Kingdom

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Source :

ISA Transactions

ISSN: 0019-0578

Year: 2022

Volume: 129

Page: 284-294

7 . 3

JCR@2022

6 . 3 0 0

JCR@2023

ESI HC Threshold:66

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

30 Days PV: 1

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