Title: Stochastic gradient-based particle filtering method for ARX models with nonlinear communication output submodel

Authors: Jianxia Feng; Donglei Lu

Addresses: Jinshen College, Nanjing Audit University, Nanjing, China; Wuxi Professional College of Science and Technology, Wuxi, China ' Jinshen College, Nanjing Audit University, Nanjing, China; Wuxi Professional College of Science and Technology, Wuxi, China

Abstract: This paper develops a stochastic gradient-based modified particle filter algorithm for an auto regressivee xogenous (ARX) model with nonlinear communication output submodel. The outputs of the ARX model are transmitted over a nonlinear communication network, while the outputs of the communication network are available. Based on the modified particle filter and the available outputs, the outputs of the ARX model can be computed, and then the unknown parameters can be estimated by the stochastic gradient algorithm. The simulation results demonstrate that the stochastic gradient-based particle filter algorithm is effective.

Keywords: system identification; stochastic gradient; particle filter; missing outputs; auto regressivee xogenous; ARX model.

DOI: 10.1504/IJMIC.2019.099823

International Journal of Modelling, Identification and Control, 2019 Vol.31 No.4, pp.331 - 336

Received: 14 Apr 2018
Accepted: 25 May 2018
Published online: 23 May 2019 *

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