A identification method of a nonlinear ARX model with variable order for nonlinear systems

Author

Hasuike, Yuya ; Izutsu, Masayuki ; Hatakeyama, S.

Author_Institution

Dept. of Robot. & Mechatron., Tokyo Denki Univ., Tokyo, Japan

fYear

2013

fDate

10-13 Nov. 2013

Firstpage

3246

Lastpage

3251

Abstract

This paper gives a identification method of new input-output model. In a identification of a nonlinear model, a nonlinear ARX model(NARX) is presented by Ohata, Furuta et.al. The NARX model consists of a set of ARX models with same orders at each output level. However, a systems order of a nonlinear system is different for each system state, usually. We propose new NARX model with variable order at a output levels. In addition, the proposed method is compared with the conventional NARX model by estimated accuracy. As a result, the conformance rate of the proposed method were larger than that by one of the NARX model. Furthermore, the mean and the variance of estimated error of the proposed method were smaller than one of the NARX model.

Keywords

autoregressive processes; estimation theory; identification; nonlinear control systems; conformance rate; conventional NARX model; estimated accuracy; estimated error; identification method; input-output model; nonlinear ARX model; nonlinear systems; system state; systems order; Accuracy; Data models; Equations; Interpolation; Mathematical model; Nonlinear systems; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE

Conference_Location

Vienna

ISSN

1553-572X

Type

conf

DOI

10.1109/IECON.2013.6699648

Filename

6699648