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Soft Computing Testing in Real Industrial Platforms for Process Intelligent Control

  • E. LarzabalEmail author
  • J. A. Cubillos
  • M. Larrea
  • E. Irigoyen
  • J. J. Valera
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 188)

Abstract

By testing advanced control techniques based on Soft Computing into industrial platforms is possible to analyse the feasibility and reliability of these implementations for being subsequently used in real industrial processes. In many cases, this fact is not taken into account for several reasons concerning with the complexity of performing hardware implementations. Hence, simulation testing becomes the last step before showing an implemented solution. The main objective of this work is to give a step beyond for achieving a more realistic test of the Intelligent Control techniques. For this reason, a first approximation of a Genetic Algorithm controller (NSGA-II) is implemented, tested, studied and compared in the stages of the controller design, and simultaneously in different industrial platforms. Most relevant results obtained in software simulation and in Hardware In the Loop (HIL) implementation are finally shown and analysed.

Keywords

Soft Computing Model Predictive Control Intelligent Control Nondominated Sort Genetic Algorithm Peripheral Component Interconnect 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • E. Larzabal
    • 1
    Email author
  • J. A. Cubillos
    • 1
  • M. Larrea
    • 1
  • E. Irigoyen
    • 1
  • J. J. Valera
    • 1
  1. 1.Intelligent Control Research GroupUniversity of the Basque Country (UPV/EHU)BilbaoSpain

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