Identification of fractional order models for electrical networks

Cheng

Int. J. Control Autom. Syst.

2011

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.

“…Select i =15 in (12). 60 frequencies logarithmically spaced in the range [0.1 10] rad/s are taken into account.…”

Section: Illustrative Examplementioning

confidence: 99%

“…Then, for the least squares problem (19), the optimal row weighted matrix W ls can be chosen as [12]:…”

Section: Choice Of Weight W Lsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Cheng

Int. J. Control Autom. Syst.

2011

“…Calculating numerically the convolution integral is reasonable for short time intervals. [8][9][10][11] These are linear circuits and are easier to simulate. Problems arise regarding the memory usage and the computation time because the time instances of the current I(t) have to be stored for a long time interval [0, t].…”

Section: Introductionmentioning

confidence: 99%

On the efficient simulation of electrical circuits with constant phase elements: The Warburg element as a test case

Athanasiou

Konkoli

2018

Circuit Theory & Apps

The constant phase Element (CPE) concept naturally emerges as a model for describing a range of electrical phenomena where ionic diffusion is involved. We suggest a new method for modelling the transient behavior of electrical circuits that contain CPE elements. Without loss of generality, we study the Warburg element to demonstrate the method, but the method can be easily extended to any CPE. Transient simulations of such elements require the numerical evaluation of a computationally expensive convolution integral that links the voltage drop across the element, with the current that passed through it. In our work we suggest a new method for reducing the computational cost of the numerical evaluation of the convolution integral. We show that the computational cost can be reduced by one order of magnitude.

The 27th Chinese Control and Decision Conference (2015 CCDC)

“…Malti et al [19] solved the problem of parameter estimation of fractional models in a bounded error context. A combination of Levenberg-Marquardt optimization and a quadratic logarithmic criterion based on the output error method was presented to model fractional order electrical element networks [20]. The relay feedback approach has been extended to a identify fractional order plus dead time model in frequency domain [21].…”

Section: Introductionmentioning

confidence: 99%

Memory identification of fractional order systems: Background and theory

Zhao

2015

This paper presents a novel work that how to determine the memory (initialization function) of fractional order systems by using the recent sampled input-output data. The background and basic theories of initialized fractional order systems are introduced. A practical algorithm is proposed to estimate the initial value of initialization function, which is adaptive to all system parameters. A P-type learning law is applied so that the initialization function can be computed accordingly. The whole process is optimized by using finite system information. The above strategy is available for both Caputo and Riemann-Liouville fractional order systems, where the initial values are applied instead of the initial conditions.