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“On-the-fly” Parameter Identification for Dynamic Systems Control, Using Interval Computations and Reduced-Order Modeling

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Fuzzy Logic in Intelligent System Design (NAFIPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 648))

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Abstract

Computer simulations of dynamic systems are really important to better understand some processes or phenomena without having to physically execute them, and/or to make offline decisions, or decisions that do not need immediate, “on-the-fly” answers in general. However, given a set of equations describing a dynamic phenomenon, wouldn’t it be nice to be able to exploit them more? Instead of simulating a situation, could we gear it or even veer it to a predefined performance? This paper is concerned with the identification of parameters of dynamic systems that ensure a specific performance or behavior. We propose to carry such computations using intervals and constraint solving techniques. However, realistically, aiming to enable such identification and decision on an on-going process or phenomena requires being able to conduct very fast computations on possibly very large systems of equations. We further propose to combine interval and constraint solving techniques with reduced-order modeling techniques to guarantee results in a practical amount of time.

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Notes

  1. 1.

    In this paper, we assume that the basis \(\varPhi \) is given.

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Acknowledgment

This work was supported by Stanford’s Army High-Performance Computing Research Center funded by the Army Research Lab, and by the National Science Foundation award #0953339.

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Authors and Affiliations

  1. Computer Science Department, College of Engineering, The University of Texas at El Paso, 500 W. University Ave, El Paso, TX, 79969-0518, USA

    Leobardo Valera, Angel Garcia Contreras & Martine Ceberio

Authors
  1. Leobardo Valera
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  2. Angel Garcia Contreras
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  3. Martine Ceberio
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Corresponding author

Correspondence to Leobardo Valera .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Reformat

  5. Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Ontario, Canada

    William Melek

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Valera, L., Contreras, A.G., Ceberio, M. (2018). “On-the-fly” Parameter Identification for Dynamic Systems Control, Using Interval Computations and Reduced-Order Modeling. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_33

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  • DOI: https://doi.org/10.1007/978-3-319-67137-6_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67136-9

  • Online ISBN: 978-3-319-67137-6

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