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Authors: Annamária R. Várkonyi-Kóczy 1 ; Attila Bencsik 1 and Antonio Ruano 2

Affiliations: 1 Institute of Mechatronics, Óbuda University, Hungary ; 2 Faculty of Science & Technology, University of Algarve, Portugal

ISBN: 978-989-8425-02-7

ISSN: 2184-2809

Keyword(s): Power plant control, Intelligent control, Situational control, Anytime modeling, Fuzzy modeling, SVD based complexity reduction, Time critical systems, Resource insufficiency.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Enterprise Information Systems ; Informatics in Control, Automation and Robotics ; Information-Based Models for Control ; Intelligent Control Systems and Optimization ; Real-Time Systems Control ; Signal Processing, Sensors, Systems Modeling and Control ; Soft Computing

Abstract: In time critical applications, anytime mode of operation offers a way to ensure continuous operation and to cope with the possibly dynamically changing time and resource availability. Soft Computing, especially fuzzy model based operation proved to be very advantageous in power plant control where the high complexity, nonlinearity, and possible partial knowledge usually limit the usability of classical methods. Higher Order Singular Value Decomposition based complexity reduction makes possible to convert different classes of fuzzy models into anytime models, thus offering a way to combine the advantages, like low complexity, flexibility, and robustness of fuzzy and anytime techniques. By this, a model based anytime control methodology can be suggested which is able to keep on continuous operation using non-exact, approximate models of the plant, thus preventing critical breakdowns in the operation. In this paper, an anytime modeling method is suggested which makes possible to use co mplexity optimized fuzzy models in control. The technique is able to filter out the redundancy of fuzzy models and can determine the near optimal non-exact model of the plant considering the available time and resources. It also offers a way to improve the granularity (quality) of the model by building in new information without complexity explosion. (More)

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Paper citation in several formats:
R. Várkonyi-Kóczy A.; Bencsik A.; Ruano A. and (2010). ANYTIME MODELS IN FUZZY CONTROL.In Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-989-8425-02-7, pages 213-220. DOI: 10.5220/0002966102130220

@conference{icinco10,
author={Annamária {R. Várkonyi{-}Kóczy} and Attila Bencsik and Antonio Ruano},
title={ANYTIME MODELS IN FUZZY CONTROL},
booktitle={Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2010},
pages={213-220},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002966102130220},
isbn={978-989-8425-02-7},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - ANYTIME MODELS IN FUZZY CONTROL
SN - 978-989-8425-02-7
AU - R. Várkonyi-Kóczy, A.
AU - Bencsik, A.
AU - Ruano, A.
PY - 2010
SP - 213
EP - 220
DO - 10.5220/0002966102130220

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