Approximation of high order integer systems by fractional order reduced-parameters models

Authors:
Rachid Mansouri;Maamar Bettayeb;Said Djennoune
Affiliations:
Laboratoire de Conception et Conduite des Systèmes de production, Mouloud Mammeri University of Tizi-Ouzou, Algeria;Electrical and Computer Engineering Department, University of Sharjah, United Arab Emirates;Laboratoire de Conception et Conduite des Systèmes de production, Mouloud Mammeri University of Tizi-Ouzou, Algeria
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2010

Citing 2
Cited 2

Analysis and design of fractional-order digital control systems

Systems Analysis Modelling Simulation
The statistics of the fractional moments: is there any chance to "read quantitatively" any randomness?

Signal Processing - Fractional calculus applications in signals and systems

Fractional models for modeling complex linear systems under poor frequency resolution measurements

Digital Signal Processing
Fractional integro-differential calculus and its control-theoretical applications. II. Fractional dynamic systems: Modeling and hardware implementation

Automation and Remote Control

Quantified Score

Hi-index	0.98

Visualization

Abstract

The approximation of a fractional system, characterized by a long memory, by an integer order transfer function, requires the use of a very high number of parameters. This characteristic is used in this paper to deal with the approximation of large order systems using a high number of parameters fractional models, but using only few parameters. Contrary to the traditional system order reduction methods which, because of reducing the system order, also reduce the number of its parameters, the use of fractional models leads to models using only very few parameters, but of infinite dimension, because of their ''long memory'' characteristics. This new use of fractional derivative is therefore named reduced-parameters modeling or model compression and is attractive for the analysis and design of large dynamical systems.