Lung Thermal Transfer System Identification With Fractional Models

Victor, Stéphane; Melchior, Pierre; Pellet, M; Oustaloup, Alain

doi:10.1109/tcst.2018.2877606

Cited by 27 publications

(11 citation statements)

References 15 publications

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“…A two‐step procedure for approximating the H‐N function was recently presented in Victor et al 20 and is based on the Oustaloup's approximation 40 . According to this approach, and for 0 <

α

< 1, the H‐N function is written as

H_{H N} false(s false) = H_{C D} false(s false) \cdot k_{1} false(s false)

where

H_{C D} false(s false) = {((), τ s + 1)}^{α \cdot β}

is a C‐D function representing the asymptotic behavior of the H‐N function while k 1 ( s ) is a correction function representing the difference between the real and the asymptotic behaviors.…”

Section: Approximation and Implementation Of The H‐n Impedance Functionmentioning

confidence: 99%

“…The question being addressed in this work is how to physically realize the H‐N model (assuming it has been found to be the most optimum fit for a given EIS data set) using normal resistor‐capacitor networks, which is not a trivial problem. In particular, we propose a novel implementation procedure based on a one‐step Padé‐based approximation method, which is far more efficient than any of the methods recently proposed 20 . To the best of our knowledge, this work is the first to show a clear passive circuit synthesis procedure for the H‐N impedance function.…”

Section: Introductionmentioning

confidence: 99%

“…Although this model has been successfully used in many cases, 17 a large number of applications requires models with additional degrees of freedom that are able to accurately fit the measured impedance magnitude and phase responses over a specific frequency range of interest. Therefore, the well‐known Cole–Cole (C‐C), Cole–Davidson (C‐D), and the more general Havriliak–Negami (H‐N) models are widely used particularly in bio‐impedance analysis 18‐20 . The three‐parameter H‐N model is given by

H_{H N} false(s false) = \frac{1}{{([], 1 + {((), τ s)}^{α})}^{β}},

where

α

and β are fractional orders (dispersion coefficients) and τ is a characteristic time‐constant.…”

Section: Introductionmentioning

confidence: 99%

“…Both methods suffer from limited accuracy and are unable to reflect the distinct contribution of the two exponents

a

, β . A more accurate method was recently proposed in Victor et al, 20 but this method is too complex and cannot be easily translated into a circuit synthesis procedure (see the following section).…”

Section: Introductionmentioning

confidence: 99%

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Passive approximations of double‐exponent fractional‐order impedance functions

Kapoulea

Psychalinos

Elwakil

2021

Circuit Theory & Apps

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Summary Double‐exponent fractional‐order impedance functions are important for modeling a wide range of biochemical materials and biological tissues. Through appropriate selection of the two exponents (fractional orders), the well‐known Havriliak–Negami, Cole–Cole, Cole–Davidson, and Debye relaxation models can be obtained as special cases. Here we show that an integer‐order Padé‐based approximation of the Havriliak–Negami function is possible to obtain and can be realized using appropriately configured Cauer/Foster resistor‐capacitor (RC) networks. Two application examples are subsequently examined: the emulation of the capacitive behavior in a polycrystalline solid electrolyte and the emulation of the impedance of four “fractal” vegetable types.

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“…A two‐step procedure for approximating the H‐N function was recently presented in Victor et al 20 and is based on the Oustaloup's approximation 40 . According to this approach, and for 0 <

α

< 1, the H‐N function is written as

H_{H N} false(s false) = H_{C D} false(s false) \cdot k_{1} false(s false)

where

H_{C D} false(s false) = {((), τ s + 1)}^{α \cdot β}

Section: Approximation and Implementation Of The H‐n Impedance Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

H_{H N} false(s false) = \frac{1}{{([], 1 + {((), τ s)}^{α})}^{β}},

where

α

and β are fractional orders (dispersion coefficients) and τ is a characteristic time‐constant.…”

Section: Introductionmentioning

confidence: 99%

“…Both methods suffer from limited accuracy and are unable to reflect the distinct contribution of the two exponents

a

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Passive approximations of double‐exponent fractional‐order impedance functions

Kapoulea

Psychalinos

Elwakil

2021

Circuit Theory & Apps

View full text Add to dashboard Cite

show abstract

“…This physical phenomena have led to the theoretical conception of constantphase element [16,29], that may be used as building blocks for circuit models. Constant-phase element may be used to model intestine tissue behavior [9], cardiac tissue [21], porous films [4] and lung behavior [14,42].…”

Section: Introductionmentioning

confidence: 99%

Long-memory recursive prediction error method for identification of continuous-time fractional models

et al. 2022

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Analytical formulas for calculating the electrical characteristics of multiparameter arbitrary configurational homogenous ladder networks

Prasanna

Mondal

2023

Circuit Theory & Apps

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Summary Most electrical systems are represented as ladder networks made up of resistances, inductances and capacitances. Electrical characteristics of these networks, such as voltages, currents and equivalent impedance, are difficult to compute because they require solving multiple differential‐algebraic equations. Further, circuit simulator‐based modelling is a time‐consuming and tedious process for simulating large networks with multiparameters present in various configuration. This paper presents generalised analytical formulae for computing the electrical properties of any multiparameter arbitrary section homogenous ladder network that can be reduced to series and shunt impedances. Circuit principles, chain matrix decomposition and linear transformation are used to derive the symbolic expressions. Simply plugging the values of the series and shunt impedances, as well as the number of sections, into the derived expression yields the impedance. Thereafter, the calculated impedances can be used to calculate the nodal voltages and mesh currents. Simulation results of a six‐section homogeneous ladder network are presented and compared with those of other existing techniques to validate the derived expressions. The derived expressions eliminate the need for recursive relations, complex integro‐differential equations, large state‐space matrices and simulator‐based circuit modelling, which are all clearly advantageous.

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Lung Thermal Transfer System Identification With Fractional Models

Cited by 27 publications

References 15 publications

Passive approximations of double‐exponent fractional‐order impedance functions

Passive approximations of double‐exponent fractional‐order impedance functions

Long-memory recursive prediction error method for identification of continuous-time fractional models

Analytical formulas for calculating the electrical characteristics of multiparameter arbitrary configurational homogenous ladder networks

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