Constrained State-Space System Identification With Application to Structural Dynamics

Sjövall, Per; McKelvey, Tomas; Abrahamsson, Thomas

doi:10.3182/20060329-3-au-2901.00209

Cited by 4 publications

(4 citation statements)

References 5 publications

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“…Constraints in the frequency domain, e.g. knowledge of the phase and slope in a frequency response function, have been used and incorporated in subspace identification [10], [14], [15], [16]. Prior information on locations of poles was found beneficial in subspace identification [17], [18].…”

Section: Introductionmentioning

confidence: 98%

Subspace identification with prior steady-state information

Alenany

Shang

Soliman

et al. 2010

The 2010 International Conference on Computer Engineering &Amp; Systems

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In system identification, the quality of data is important for obtaining good models, but there are situations where the available data are highly corrupted with noise. However, some prior information about the system to be identified, such as dc gain and settling time, may be available to obtain improved model identification despite data noise. In this paper, a subspace identification scheme incorporating known dc gain is investigated. The prior process information is incorporated into system identification through using the least square with the equality constraint that the sum of impulse response parameters is equal to the dc gain. In comparison with the existing approaches, the proposed identification strategy provides unbiased parameter estimations, is applicable to Multi-Input Multi-Output (MIMO) systems, and is computationally efficient.

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Section: Introductionmentioning

confidence: 98%

Subspace identification with prior steady-state information

Alenany

Shang

Soliman

et al. 2010

The 2010 International Conference on Computer Engineering &Amp; Systems

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“…Using this inequality (17) and taking integration on both sides of (9) with (6)- (8) or (16) with (13)- (15) yield…”

Section: Properties and Stabilities For Two Estimatorsmentioning

confidence: 99%

On-Line Model Parameter Estimations for Time-Delay Systems

Park

Han

Kwon

2013

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper concerns a problem of on-line model parameter estimations for multiple time-delay systems. In order to estimate unknown model parameters from measured state variables, we propose two schemes using Lyapunov's direct method, called parallel and series-parallel model estimators. It is shown through a numerical example that the proposed parallel and series-parallel model estimators can be effective when sufficiently rich inputs are applied.

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“…• The problem of identifying the state-space model of a structural dynamical system satisfying some constraints can be translated to the problem of minimizing a rational function subject to some rational constraints [9]. The main challenge in this problem is how to find the global solution as opposed to a local one.…”

Section: Introductionmentioning

confidence: 99%

Rational optimization using sum-of-squares techniques

Lavaei

Sojoudi

Aghdam

2007

2007 46th IEEE Conference on Decision and Control

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Abstract-Motivated by many control applications, this paper deals with the global solutions of unconstrained optimization problems. First, a simple SOS method is presented to find the infimum of a polynomial, which can be handled efficiently using the relevant software tools. The main idea of this method is to introduce a perturbation variable whose approaching to zero results in a solution with any arbitrary precision. The proposed technique is then extended to the case of rational functions. The primary advantages of this approach over the existing ones are its simplicity and capability of treating problems for which the existing methods are not efficient, as demonstrated in three numerical examples.

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Constrained State-Space System Identification With Application to Structural Dynamics

Cited by 4 publications

References 5 publications

Subspace identification with prior steady-state information

Subspace identification with prior steady-state information

On-Line Model Parameter Estimations for Time-Delay Systems

Rational optimization using sum-of-squares techniques

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