Advances in System Identification Using Fractional Models

Malti, Rachid; Victor, Stéphane; Oustaloup, Alain

doi:10.1115/1.2833910

Cited by 104 publications

(44 citation statements)

References 5 publications

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“…Some researchers focus on it, and have presented several identification methods both in time domain and in frequency domain. In time domain, Rachid et al [4] proposed an identification method based on fractional Poisson filter with respect to equation error and output error. The identification of continuous order distribution systems was studied by Hartley et al [5] in time domain, and a least square result was obtained.…”

Section: Introductionmentioning

confidence: 99%

Frequency domain subspace identification of commensurate fractional order input time delay systems

Wang

Cheng

Wang

2011

Int. J. Control Autom. Syst.

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A frequency domain subspace identification of fractional order systems with input timedelay is studied in this paper. A new identification method, which combines the merits of differential evolution (DE) algorithm and subspace identification algorithm in frequency domain, is presented. For the optimal search of fractional commensurate differential order and time delay parameters, the DE algorithm is applied. For fixed fractional commensurate differential order and time delay, subspace method is performed to obtain the state space model. Simulation results validate the proposed fractional order system identification method.

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Section: Introductionmentioning

confidence: 99%

Frequency domain subspace identification of commensurate fractional order input time delay systems

Wang

Cheng

Wang

2011

Int. J. Control Autom. Syst.

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“…Recently, Malti et al (2008b) have extended the concept of optimal IV methods to fractional systems. For an overview of these identification methods refer to Malti et al (2008a).…”

Section: Introductionmentioning

confidence: 99%

Subspace method for continuous-time fractional system identification

Thomassin

Malti

2009

IFAC Proceedings Volumes

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To cite this version:Magalie Thomassin, Rachid Malti. Abstract: The aim of this paper is to develop a subspace method for state-space identification of continuous-time systems using fractional commensurate models. As compared to the classical state-space representation, the commensurate differentiation order must be estimated besides the state-space matrices. The latter are estimated with conventional subspace-based techniques using QR and singular value decompositions, whereas the commensurate order is estimated using nonlinear programming. This is the first method developed for multi-input multi-output system identification of fractional models. The performances are demonstrated by simulations at various signal-to-noise ratios assuming a known then an unknown commensurate order.

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“…where λx(t), λu(t) and λe(t) correspond to the states, the inputs and the noise prefiltered by Λ in (9). Then, from (13), it is found by recursion that:…”

Section: Fractional Systemsmentioning

confidence: 99%

“…Recently, Malti et al [8] have extended the concept of optimal IV methods to fractional systems. For an overview of these identification methods refer to [9].…”

Section: Introductionmentioning

confidence: 99%