Treffer: A New Orthogonal Least Squares Identification Method for a Class of Fractional Hammerstein Models

Title:
A New Orthogonal Least Squares Identification Method for a Class of Fractional Hammerstein Models
Source:
Algorithms ; Volume 18 ; Issue 4 ; Pages: 201
Publisher Information:
Multidisciplinary Digital Publishing Institute
Publication Year:
2025
Collection:
MDPI Open Access Publishing
Document Type:
Fachzeitschrift text
File Description:
application/pdf
Language:
English
Relation:
Algorithms for Multidisciplinary Applications; https://dx.doi.org/10.3390/a18040201
DOI:
10.3390/a18040201
Accession Number:
edsbas.AF3BCA8F
Database:
BASE

Weitere Informationen

It is known that fractional-order models can effectively represent complex high-order systems with fewer parameters. This paper focuses on the identification of a class of multiple-input single-output fractional Hammerstein models. When the commensurate order is assumed to be known, a greedy orthogonal least squares method is proposed to simultaneously identify the parameters and system orders, combined with a stopping rule based on the Bayesian information criterion. Subsequently, the commensurate order is determined by minimizing the normalized output error. The proposed method is validated by applying it to identify a CD-player arm system.