ON THE DYNAMICS OF LOCAL LINEAR MODEL NETWORKS WITH ORTHONORMAL BASIS FUNCTIONS

摘要

This paper deals with local linear model networks for nonlinear system identification. It compares the standard nonlinear autoregressive with exogenous input (NARX) model structure with the new nonlinear orthonormal basis functions (NOBF) model structure. In particular, the dynamics of interpolated local ARX and OBF models are studied and significant advantages for the NOBF approach are pointed out. Furthermore, the dynamic effect of scheduling variables in local linear model networks based on OBFs is investigated. It is concluded that the NOBF approach is a promising alternative for nonlinear system identification and deserves more attention in the future.