Orthonormal basis selection for LPV system identification, the Fuzzy-Kolmogorov c-Max approach

A fuzzy clustering approach is developed to select pole locations for orthonormal basis functions (OBFs), used for identification of linear parameter varying (LPV) systems. The identification approach is based on interpolation of locally identified linear time invariant (LTI) models, using globally fixed OBFs. Selection of the optimal OBF structure, that guarantees the least worst-case local modelling error in an asymptotic sense, is accomplished through the fusion of the Kolmogorov n-width (KnW) theory and fuzzy c-means (FcM) clustering of observed sample system poles