Parameter Estimation of Two-Dimensional Linear Differential Systems via Fourier Based Modulation Function

Sadabadi, M. S.; Shafiee, Masoud; Karrari, M.

doi:10.3182/20080706-5-kr-1001.02437

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…(2) An another approach to get rid off the initial and boundary condition problem consists in using a modulating function based method (see e.g. Sadabadi et al [2008b]). A clear advantage of the modulating function methods is that because of their properties, the effects of initial and boundary conditions disappear in the estimation model equation.…”

Section: Fig 2 Estimation Areamentioning

confidence: 99%

“…PDE model identification based on continuous space-time separation of the signals is also proposed in Li and Qi [2010]. The input/output signals are in this case expressed in a basis of polynomial functions such as wavelet (Sadabadi et al [2008a]), Walsh series (Tzafestas [1978]) or Fourier series (Sadabadi et al [2008b]). It is also possible to pass through a filtering method involving integrals (Sagara et al [1990]).…”

Section: Introductionmentioning

confidence: 99%

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Instrumental variable methods for identifying partial differential equation models of distributed parameter systems

Schorsch

Garnier²,

Gilson³

2012

IFAC Proceedings Volumes

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This paper presents instrumental variable methods for identifying partial differential equation models of distributed parameter systems in presence of output measurement noise. Two instrumental variable-based techniques are proposed to handle this continuous-time model identification problem: a basic one using input-only instruments and a more sophisticated refined instrumental variable method. Numerical examples are presented to illustrate and compare the performances of the proposed approaches.

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Section: Fig 2 Estimation Areamentioning

confidence: 99%