System identification using a multi-model approach: modelcomplexity reduction
Résumé
A multi-model provides a powerful tool fornon-linear dynamic systems identification. Theoreticalstudies have shown that any continuous function on acompact domain can be approximated arbitrarily well by afuzzy model. However, due to the curse of dimensionality,building a multi-model is a difficult task in practicewithout some precautions. Hence, only the simpleststructure fitting the training data must be chosen in orderto keep good generalisation capabilities of the model. Inthis paper, parsimony is obtained by removing redundantand/or useless rules. The proposed approach has beensuccessfully illustrated by simulation examples from literature.