Non-linear Robust Identification: Application to a Thermal Process

  • Authors:

  • J. M. Herrero;X. Blasco;M. Martínez;J. V. Salcedo

  • Affiliations:

  • Predictive Control and Heuristic Optimization Group, Department of Systems Engineering and Control, Polytechnic University of Valencia, Spain;Predictive Control and Heuristic Optimization Group, Department of Systems Engineering and Control, Polytechnic University of Valencia, Spain;Predictive Control and Heuristic Optimization Group, Department of Systems Engineering and Control, Polytechnic University of Valencia, Spain;Predictive Control and Heuristic Optimization Group, Department of Systems Engineering and Control, Polytechnic University of Valencia, Spain

  • Venue:
  • IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
  • Year:
  • 2007

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Abstract

In this article, a methodology to obtain the Feasible Parameter Set (FPS) and a nominal model in a non-linear robust identification problem is presented. Several norms are taken into account simultaneously to define the FPSwhich improves the model quality but, as counterpart, it increases the optimization problem complexity. To determine the FPSa multimodal optimization problem with an infinite number of minima, which constitute the FPS, is presented and a special evolutionary algorithm (驴驴GA) is used to characterize it. Finally, an application to a thermal process identification, where ||·||驴and ||·||1norms have been considered simultaneously, is presented to illustrate the technique.