کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
712947 | 892159 | 2015 | 6 صفحه PDF | دانلود رایگان |
In this paper we deal with identification of nonlinear systems which are modelled by fuzzy rule-based models that do not assume fixed partitioning of the space of antecedent variables. We first present an alternative way of describing local density in the cloud-based evolving systems. The Mahalanobis distance among the data samples is used which leads to the density that is more suitable when the data are scattered around the input-output surface. All the algorithms for the identification of the cloud parameters are given in a recursive form which is necessary for the implementation of an evolving system. It is also shown that a simple linearised model can be obtained without identification of the consequent parameters. All the proposed algorithms are illustrated on a simple simulation model of a static system.
Journal: IFAC-PapersOnLine - Volume 48, Issue 10, 2015, Pages 129-134