Volume 13, Issue 4 (2014)
MJEE 2014, 13(4): 17-28 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Safarinejadian B, Asad M, Torabi Jahromi A. A Hierarchical Identification Method for SISO Fractional-order State-space Systems. MJEE 2014; 13 (4) :17-28
URL: http://mjee.modares.ac.ir/article-17-6421-en.html
URL: http://mjee.modares.ac.ir/article-17-6421-en.html
1- Associate Professor, Control Engineering Department, Shiraz University of Technology, Shiraz, Iran.
safarinejad@sutech.ac.ir
2- MSc, Control Engineering Department, Shiraz University of Technology, Shiraz, Iran.
3- Assistant Professor, Electrical and Electronic Engineering Department, Persian Gulf University of Bushehr, Iran.
2- MSc, Control Engineering Department, Shiraz University of Technology, Shiraz, Iran.
3- Assistant Professor, Electrical and Electronic Engineering Department, Persian Gulf University of Bushehr, Iran.
Abstract: (7343 Views)
This paper proposes a new hierarchical identification method for fractional-order systems. In this method, a SISO (single input, single output) state space model has been considered in which parameters and also state variables should be estimated. By using a linear transformation and a shift operator, the system will be transformed into a form appropriate for identification of a fractional-order system. Then, the unknown parameters will be identified through a recursive least squares method and the states will be estimated using a fractional order Kalman filter. This identification method is based on the hierarchical identification principle that reduces the computational burden and is easy to implement on computer. The promising performance of the proposed method is verified using two stable fractional-order systems.
Keywords: Fractional order systems, fractional order Kalman filter, recursive identification, hierarchical identification principle
Received: 2016/08/22 | Accepted: 2014/01/21 | Published: 2016/08/22
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |