A Time-Domain Approach to Continuous-Time Model Identification of Highly-Resonant Wide-Band Systems

Gamier, H.; Goodwill, G.C.; Welsh, James S.

doi:10.1016/s1474-6670(17)31144-8

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…3) One advantage of using an IV technique is that even if the noise model is miss-specified, the resulting IV estimates are still consistent. 4) The flbf-iv method may be related to the approach developed in the time-domain identification in [4]. However, it has the advantage of not introducing the additional estimation of signal initial conditions terms.…”

Section: Remarksmentioning

confidence: 99%

Frequency-domain instrumental variable based method for wide band system identification

Gilson

Welsh

Garnier

2013

2013 American Control Conference

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The aim of this paper is to propose an instrumental variable (IV) solution for wide-band frequency domain identification. The focus is first on the extension of the refined IV method for continuous-time model identification to the frequency domain. Then, an iterative IV scheme coupled with an appropriate frequency localising basis function is developed to provide consistent results in the case of highly resonant wide-band systems. Finally, to illustrate the performance of the proposed approach, a representative Monte Carlo simulation as well as a practical case are presented.

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Section: Remarksmentioning

confidence: 99%

Frequency-domain instrumental variable based method for wide band system identification

Gilson

Welsh

Garnier

2013

2013 American Control Conference

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“…In this section we present a brief review of direct least squares-based identification of continuous-time models [8,9,7] when the data are noise-free. Next, we examine the additional issues involved in EIV problems.…”

Section: Least Squares Identificationmentioning

confidence: 99%

“…Due to numerical errors introduced in the digital simulation of the continuous-time filtering, (7) does not hold exactly 4 . Therefore, it is required to solve (7) [see also (2) and (3)] in a LS or total least squares sense.…”

Section: Noise-free Casementioning

confidence: 99%

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Identification of continuous-time errors-in-variables models

Mahata

Garnier

2006

Automatica

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A novel direct approach for identifying continuous-time linear dynamic errors-in-variables models is presented in this paper. The effects of the noise on the state-variable filter outputs are analyzed. Subsequently, a few algorithms to obtain consistent continuous-time parameter estimates in the errors-invariables framework are derived. It is also possible to design search-free algorithms within our framework. The algorithms can be used for nonuniformly sampled data. The asymptotic distributions of the estimates are derived. The performances of the proposed algorithms are illustrated with some numerical simulation examples.

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A Frequency Localizing Basis Function-Based IV Method for Wideband System Identification

Gilson

Welsh

Garnier

2018

IEEE Trans. Contr. Syst. Technol.

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A Time-Domain Approach to Continuous-Time Model Identification of Highly-Resonant Wide-Band Systems

Cited by 3 publications

References 8 publications

Frequency-domain instrumental variable based method for wide band system identification

Frequency-domain instrumental variable based method for wide band system identification

Identification of continuous-time errors-in-variables models

A Frequency Localizing Basis Function-Based IV Method for Wideband System Identification

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