Performance Evaluation of Iterative Signal Design for System Identification

Md. Tanjil Sarker; Ai Hui Tan; Timothy Tzen Vun Yap

doi:10.1109/I2CACIS54679.2022.9815488

Performance Evaluation of Iterative Signal Design for System Identification

Md. Tanjil Sarker, Ai Hui Tan, Timothy Tzen Vun Yap

School of Mathematical & Computer Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

In this paper, iterative system identification is investigated where the amplitude spectra of the perturbation signals are optimised according to the present estimate of the model parameters. The iterative signal design is compared for single-input single-output (SISO) open loop systems grouped into six different categories based on the system order and dynamic characteristic. Three different signal-to-noise ratios (SNRs) are tested. The performance of the iterative signal design is assessed by taking the ratios of the performance measures of the estimated and initial models to the actual model for a single iteration. These performance measures are defined based on errors in the frequency response. It was found that the iterative signal design is very effective in reducing the model error, except for high order lowpass systems.

Original language	English
Title of host publication	2022 IEEE International Conference on Automatic Control and Intelligent Systems
Publisher	IEEE
Pages	203-208
Number of pages	6
ISBN (Electronic)	9781665495813
DOIs	https://doi.org/10.1109/I2CACIS54679.2022.9815488
Publication status	Published - 8 Jul 2022
Event	2022 IEEE International Conference on Automatic Control and Intelligent Systems - Shah Alam, Malaysia Duration: 25 Jun 2022 → …

Conference

Conference	2022 IEEE International Conference on Automatic Control and Intelligent Systems
Abbreviated title	I2CACIS 2022
Country/Territory	Malaysia
City	Shah Alam
Period	25/06/22 → …

Keywords

amplitude spectra
iterative design
perturbation signals
signal design
system identification

ASJC Scopus subject areas

Artificial Intelligence
Information Systems and Management
Control and Systems Engineering
Control and Optimization

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10.1109/I2CACIS54679.2022.9815488

Cite this

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title = "Performance Evaluation of Iterative Signal Design for System Identification",

abstract = "In this paper, iterative system identification is investigated where the amplitude spectra of the perturbation signals are optimised according to the present estimate of the model parameters. The iterative signal design is compared for single-input single-output (SISO) open loop systems grouped into six different categories based on the system order and dynamic characteristic. Three different signal-to-noise ratios (SNRs) are tested. The performance of the iterative signal design is assessed by taking the ratios of the performance measures of the estimated and initial models to the actual model for a single iteration. These performance measures are defined based on errors in the frequency response. It was found that the iterative signal design is very effective in reducing the model error, except for high order lowpass systems.",

keywords = "amplitude spectra, iterative design, perturbation signals, signal design, system identification",

author = "Sarker, {Md. Tanjil} and Tan, {Ai Hui} and Yap, {Timothy Tzen Vun}",

note = "Funding Information: ACKNOWLEDGMENT The first author acknowledges financial sponsorship from the Multimedia University, Malaysia under the Graduate Research Assistantship scheme and the ICT Division, Bangladesh under the Research Fellowship scheme. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2022 ; Conference date: 25-06-2022",

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doi = "10.1109/I2CACIS54679.2022.9815488",

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Sarker, MT, Tan, AH & Yap, TTV 2022, Performance Evaluation of Iterative Signal Design for System Identification. in 2022 IEEE International Conference on Automatic Control and Intelligent Systems. IEEE, pp. 203-208, 2022 IEEE International Conference on Automatic Control and Intelligent Systems, Shah Alam, Malaysia, 25/06/22. https://doi.org/10.1109/I2CACIS54679.2022.9815488

TY - GEN

T1 - Performance Evaluation of Iterative Signal Design for System Identification

AU - Sarker, Md. Tanjil

AU - Tan, Ai Hui

AU - Yap, Timothy Tzen Vun

N1 - Funding Information: ACKNOWLEDGMENT The first author acknowledges financial sponsorship from the Multimedia University, Malaysia under the Graduate Research Assistantship scheme and the ICT Division, Bangladesh under the Research Fellowship scheme. Publisher Copyright: © 2022 IEEE.

PY - 2022/7/8

Y1 - 2022/7/8

N2 - In this paper, iterative system identification is investigated where the amplitude spectra of the perturbation signals are optimised according to the present estimate of the model parameters. The iterative signal design is compared for single-input single-output (SISO) open loop systems grouped into six different categories based on the system order and dynamic characteristic. Three different signal-to-noise ratios (SNRs) are tested. The performance of the iterative signal design is assessed by taking the ratios of the performance measures of the estimated and initial models to the actual model for a single iteration. These performance measures are defined based on errors in the frequency response. It was found that the iterative signal design is very effective in reducing the model error, except for high order lowpass systems.

AB - In this paper, iterative system identification is investigated where the amplitude spectra of the perturbation signals are optimised according to the present estimate of the model parameters. The iterative signal design is compared for single-input single-output (SISO) open loop systems grouped into six different categories based on the system order and dynamic characteristic. Three different signal-to-noise ratios (SNRs) are tested. The performance of the iterative signal design is assessed by taking the ratios of the performance measures of the estimated and initial models to the actual model for a single iteration. These performance measures are defined based on errors in the frequency response. It was found that the iterative signal design is very effective in reducing the model error, except for high order lowpass systems.

KW - amplitude spectra

KW - iterative design

KW - perturbation signals

KW - signal design

KW - system identification

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M3 - Conference contribution

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EP - 208

BT - 2022 IEEE International Conference on Automatic Control and Intelligent Systems

PB - IEEE

T2 - 2022 IEEE International Conference on Automatic Control and Intelligent Systems

Y2 - 25 June 2022

ER -

Performance Evaluation of Iterative Signal Design for System Identification

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Keywords

ASJC Scopus subject areas

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