Title: A modified model decomposition identification for bilinear-in-parameter systems

Authors: Huibo Chen; Jiangbo Fan; Jing Li

Addresses: School of Electrical Engineering and Automation, Henan Institute of Technology, Xinxiang, Henan, China ' School of Electrical Engineering, Sanmenxia Polytechnic, Sanmenxia, Henan, China ' School of Intelligent Engineering, Henan Institute of Technology, Xinxiang, Henan, China

Abstract: The so-called bilinear-in-parameter models are usually derived from the block-oriented nonlinear models and identified by different methods. Inspired by the model decomposition-based identification technique, this paper develops a recursive least squares algorithm to estimated the model parameters and obtained a global convergence which are shown by a simulation example.

Keywords: identification; bilinear model; least squares.

DOI: 10.1504/IJMIC.2019.103662

International Journal of Modelling, Identification and Control, 2019 Vol.32 No.3/4, pp.258 - 263

Received: 18 Jan 2019
Accepted: 07 Mar 2019

Published online: 18 Nov 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article