A Linear Robustly Convergent Interpolatory Algorithm For System Identification

Er-Wei Bai; Sundar Raman

doi:10.23919/ACC.1992.4792732

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Conference proceeding

A Linear Robustly Convergent Interpolatory Algorithm For System Identification

Er-Wei Bai and Sundar Raman

1992 American Control Conference, Vol.4, pp.3165-3169

American Control Conference, 1992 (Chicago, Illinois, 06/24/1992 - 06/26/1992)

06/1992

DOI: 10.23919/ACC.1992.4792732

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Abstract

This paper presents a linear, robustly convergent interpolatory algorithm for system identification in the presence of bounded noise. The proposed algorithm converges to the actual, but unknown system in frequency domain in the noise free case and maintains the robust convergence result in the face of bounded noise. This robustness property distinguishes the proposed linear algorithm from other existing linear schemes.

Polynomials

Convergence

Frequency estimation

Interpolation

Lagrangian functions

Noise robustness

Robust control

System identification

Tellurium

Tin

Details

Title: Subtitle: A Linear Robustly Convergent Interpolatory Algorithm For System Identification
Creators: Er-Wei Bai - University of Iowa
Sundar Raman - University of Iowa
Resource Type: Conference proceeding
Publication Details: 1992 American Control Conference, Vol.4, pp.3165-3169
Conference: American Control Conference, 1992 (Chicago, Illinois, 06/24/1992 - 06/26/1992)
Publisher: IEEE
DOI: 10.23919/ACC.1992.4792732
ISSN: 0743-1619
eISSN: 2378-5861
Language: English
Date published: 06/1992
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984198017102771

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