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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2010: Trends in Applied Intelligent Systems pp 11–20Cite as

Transition State Layer in the Immune Inspired Optimizer

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6096))

Abstract

The SILO (Stochastic Immune Layer Optimizer) system is a novel, immune inspired solution for an on-line optimization of a large-scale industrial processes. Three layers of optimization algorithm were presented in previous papers. Each layer represents a different strategy of steady state optimization of the process. New layer of the optimization algorithm is presented in this paper. The new Transition State layer is responsible for efficient operation of the optimization system during essential process state transitions. New results from SILO implementation in South Korean power plant are presented. They confirm high efficiency of the SILO optimizer in solving technical problems.

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References

  1. Wojdan, K., Swirski, K.: Immune Inspired Optimizer of Combustion Process in Power Boiler. In: Okuno, H.G., Ali, M. (eds.) IEA/AIE 2007. LNCS (LNAI), vol. 4570, pp. 1022–1031. Springer, Heidelberg (2007)

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  2. Wojdan, K., Swirski, K., Warchol, M., Maciorowski, M.: Maintaining Good Conditioning of Model Identification Task in Immune Inspired On-line Optimizer of an Industrial Process. Engineering Letters 17(2), 93–100 (2009)

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  3. Tatjewski, P.: Advanced Control of Industrial Processes: Structures and Aglorithms. Springer, London (2007)

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  4. Jacobs, O.L.R., Wonham, W.M.: Extremum Control in the Presence of Noise. International Journal of Electronics 11(3), 193–211 (1961)

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Author information

Authors and Affiliations

  1. Institute of Heat Engineering, Warsaw University of Technology, Poland

    Konrad Wojdan & Konrad Swirski

  2. Institute of Control and Computational Engineering, Warsaw University of Technology, Poland

    Michal Warchol

Authors
  1. Konrad Wojdan
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  2. Konrad Swirski
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  3. Michal Warchol
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Editor information

Editors and Affiliations

  1. Dept. of Computing and Numerical Analysis, University of Cordoba, Campus Universitario de Rabanales, Einstein Building, 3rd floor, 14071, Cordoba, Spain

    Nicolás García-Pedrajas

  2. Dept. of Computer Science and Artificial Intelligence, ETS de Ingenierias Informática y de Telecomunicación, University of Granada, 18071, Granada, Spain

    Francisco Herrera

  3. School of Computing, University of the West of Scotland, PA1 2BE, Paisley, UK

    Colin Fyfe

  4. Dept. Computer Science and Artificial Intelligence, ETS de Ingenierias Informática y de Telecomunicación, University of Granada, 18071, Granada, Spain

    José Manuel Benítez

  5. Department of Computer Science, Texas State University-San Marcos, 601 University Drive, TX 78666-4616, San Marcos, USA

    Moonis Ali

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© 2010 Springer-Verlag Berlin Heidelberg

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Cite this paper

Wojdan, K., Swirski, K., Warchol, M. (2010). Transition State Layer in the Immune Inspired Optimizer. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13022-9_2

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  • DOI: https://doi.org/10.1007/978-3-642-13022-9_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13021-2

  • Online ISBN: 978-3-642-13022-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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