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Model Order Reduction: A Comparison between Integer and Non-Integer Order Systems Approaches

Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, 95125 Catania, Italy
Institute of Engineering, Polytechnic of Porto, 4200-072 Porto, Portugal
Dipartimento di Ingegneria, University of Messina, 98121 Messina, Italy
Author to whom correspondence should be addressed.
Entropy 2019, 21(9), 876;
Received: 14 August 2019 / Revised: 29 August 2019 / Accepted: 6 September 2019 / Published: 9 September 2019
(This article belongs to the Special Issue The Fractional View of Complexity)
In this paper, classical and non-integer model order reduction methodologies are compared. Non integer order calculus has been used to generalize many classical control strategies. The property of compressing information in modelling systems, distributed in time and space, and the capability of describing long-term memory effects in dynamical systems are two features suggesting also the application of fractional calculus in model order reduction. In the paper, an open loop balanced realization is compared with three approaches based on a non-integer representation of the reduced system. Several case studies are considered and compared. The results confirm the capability of fractional order systems to capture and compress the dynamics of high order systems. View Full-Text
Keywords: fractional calculus; model order reduction; non-convex optimization fractional calculus; model order reduction; non-convex optimization
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Caponetto, R.; Machado, J.T.; Murgano, E.; Xibilia, M.G. Model Order Reduction: A Comparison between Integer and Non-Integer Order Systems Approaches. Entropy 2019, 21, 876.

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