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 FPS which improves the model quality but, as counterpart, it increases the optimization problem complexity. To determine the FPS a multimodal optimization problem with an infinite number of minima, which constitute the FPS, is presented and a special evolutionary algorithm (ε−GA) is used to characterize it. Finally, an application to a thermal process identification, where ||·|| ∞ and ||·||1 norms have been considered simultaneously, is presented to illustrate the technique.
Partially supported by MEC (Spanish government) and FEDER funds: projects DPI2005-07835, DPI2004-8383-C03-02 and GVA-026.
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Herrero, J.M., Blasco, X., Martínez, M., Salcedo, J.V. (2007). Non-linear Robust Identification: Application to a Thermal Process. In: Mira, J., Álvarez, J.R. (eds) Bio-inspired Modeling of Cognitive Tasks. IWINAC 2007. Lecture Notes in Computer Science, vol 4527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73053-8_46
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DOI: https://doi.org/10.1007/978-3-540-73053-8_46
Publisher Name: Springer, Berlin, Heidelberg
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