14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract

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Paper ThA1.3

Li, Kang (Queen's Univ. Belfast), Peng, Jian-Xun (Queen's Univ. Belfast), Bai, Er-Wei (Univ. of Iowa)

A Two-Stage Algorithm for Identification of Nonlinear Dynamic Systems

Scheduled for presentation during the Invited Session "Nonlinear System Identification I" (ThA1), Thursday, March 30, 2006, 11:30−11:50, Concert Hall

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 22, 2018

Keywords Nonlinear System Identification, Nonparametric Methods

Abstract

A two-stage algorithm is proposed for fast identification of optimal linear-in-the-parameters models for nonlinear dynamic systems. In the first stage, an initial model is selected from a significant number of candidates, using a stepwise forward procedure. The significance of each selected model term is reviewed iteratively at the second stage using a fast review procedure and insignificant terms are then replaced, resulting in a locally optimised compact model. The contribution is that both the forward and backward model selection is performed within a well-defined regression context, leading to significantly reduced computational complexity. The computational complexity analysis confirms the arithmetic efficiency and the simulation results demonstrate the effectiveness.