Fractional order state space canonical model identification using fractional order information filter

Author

Safarinejadian, Behrouz ; Asad, Mojtaba

Author_Institution

Shiraz Univ. of Technol., Shiraz, Iran

fYear

2015

fDate

3-5 March 2015

Firstpage

65

Lastpage

70

Abstract

In the present paper the identification and estimation problem of a fractional order state space system will be addressed. This paper presents a fractional order information filter and also a hierarchical identification algorithm to identify and estimate parameters and states of a fractional order system. Then, merging this algorithm with fractional order information filter, a novel identification method based on hierarchical identification theory is introduced to reduce the computational complexity. Finally, the applicability and performance of this platform on an exemplary system is examined.

Keywords

computational complexity; filtering theory; parameter estimation; state estimation; state-space methods; computational complexity; estimation problem; fractional order information filter; fractional order state space canonical model identification; fractional order state space system; hierarchical identification algorithm; hierarchical identification theory; identification method; parameters estimation; states estimation; Computational modeling; Information filters; Kalman filters; Mathematical model; Parameter estimation; State estimation; Fractional Order Systems; Fractional Order information filter; Hierarchical Identification Principle; Recursive Identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on

Conference_Location

Mashhad

Print_ISBN

978-1-4799-8817-4

Type

conf

DOI

10.1109/AISP.2015.7123479

Filename

7123479