A linear interpolatory algorithm for robust system identification with corrupted measurement data

Author

Bai, Er-Wei ; Raman, Sundar

Author_Institution

Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA

Volume

38

Issue

8

fYear

1993

fDate

8/1/1993 12:00:00 AM

Firstpage

1236

Lastpage

1241

Abstract

A linear, robustly convergent interpolatory algorithm for system identification in the presence of bounded noise is presented. The algorithm converges in the actual, but unknown, system in the frequency domain in the noise-free case and maintains the robust convergence result in the face of bounded noise. This robustness property distinguishes the algorithm from existing linear schemes. A key idea of this robust linear algorithm is that the approximation is separated into real and imaginary parts and into Fejer (Hermite) interpolation. Because of the Fejer interpolation the data points are required at the Chebyshev points

Keywords

convergence; identification; interpolation; stability; Chebyshev points; Fejer interpolation; Hermite interpolation; bounded noise; corrupted measurement data; frequency domain; linear interpolatory algorithm; noise-free; robust system identification; Automatic control; Chebyshev approximation; Circuit stability; Control systems; Feedback; Linear systems; Noise robustness; Notice of Violation; Stability analysis; System identification;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.233158

Filename

233158