Dynamic neural units for nonlinear dynamic systems identification

Abstract

An attempt has been made to establish a time-discrete neuron model which is applied to build Radial Basis Function mad Multilayer petceptron networks with distributed dynamics, The well-known delta-rule is extended to the dynamic delta-rule in order to optimize network paranmters. Both network types were used to identify empirical, parametrical models of a turboeharger of a Diesel engine which comply with the demanded accuracy properties to a high degree. The performance of both network types is compared according to required number of parameters, approximation accuracy and computational effort.