Abstract
This paper presents a new method to identify unknown parameters of linear fractional order systems by discretizing it at the Gauss-Lobatto-Chebyshev collocation points. The proposed spectral parametric estimation method benefits from the spectral method exponential convergence feature and results in more accuracy in the estimated parameters and less computational time. The advantages of using the spectral parameter estimation method are shown in two examples. In the first example, a batch of five isothermal creep experimental data for an epoxy is used to estimate a simple solid viscoelastic model with fractional order. In the second example, the state matrix and fractional orders of a linear system with non-commensurate fractional order are estimated by using its input-output data disturbed by unknown white Gaussian measurement noise.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 American Control Conference, ACC 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2772-2777 |
| Number of pages | 6 |
| Volume | 2016-July |
| ISBN (Electronic) | 9781467386821 |
| DOIs | |
| State | Published - Jul 28 2016 |
| Event | 2016 American Control Conference, ACC 2016 - Boston, United States Duration: Jul 6 2016 → Jul 8 2016 |
Other
| Other | 2016 American Control Conference, ACC 2016 |
|---|---|
| Country | United States |
| City | Boston |
| Period | 7/6/16 → 7/8/16 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
The spectral parameter estimation method for parameter identification of linear fractional order systems. / Dabiri, Arman; Nazari, Morad; Butcher, Eric.
2016 American Control Conference, ACC 2016. Vol. 2016-July Institute of Electrical and Electronics Engineers Inc., 2016. p. 2772-2777 7525338.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - The spectral parameter estimation method for parameter identification of linear fractional order systems
AU - Dabiri, Arman
AU - Nazari, Morad
AU - Butcher, Eric
PY - 2016/7/28
Y1 - 2016/7/28
N2 - This paper presents a new method to identify unknown parameters of linear fractional order systems by discretizing it at the Gauss-Lobatto-Chebyshev collocation points. The proposed spectral parametric estimation method benefits from the spectral method exponential convergence feature and results in more accuracy in the estimated parameters and less computational time. The advantages of using the spectral parameter estimation method are shown in two examples. In the first example, a batch of five isothermal creep experimental data for an epoxy is used to estimate a simple solid viscoelastic model with fractional order. In the second example, the state matrix and fractional orders of a linear system with non-commensurate fractional order are estimated by using its input-output data disturbed by unknown white Gaussian measurement noise.
AB - This paper presents a new method to identify unknown parameters of linear fractional order systems by discretizing it at the Gauss-Lobatto-Chebyshev collocation points. The proposed spectral parametric estimation method benefits from the spectral method exponential convergence feature and results in more accuracy in the estimated parameters and less computational time. The advantages of using the spectral parameter estimation method are shown in two examples. In the first example, a batch of five isothermal creep experimental data for an epoxy is used to estimate a simple solid viscoelastic model with fractional order. In the second example, the state matrix and fractional orders of a linear system with non-commensurate fractional order are estimated by using its input-output data disturbed by unknown white Gaussian measurement noise.
UR - http://www.scopus.com/inward/record.url?scp=84992161897&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84992161897&partnerID=8YFLogxK
U2 - 10.1109/ACC.2016.7525338
DO - 10.1109/ACC.2016.7525338
M3 - Conference contribution
AN - SCOPUS:84992161897
VL - 2016-July
SP - 2772
EP - 2777
BT - 2016 American Control Conference, ACC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -