USING NEURAL NETWORKS FOR THE IDENTIFICATION OF A CLASS OF HYBRID DYNAMIC SYSTEMS

摘要

This paper addresses the problem of the identification of Hybrid Dynamic System (HDS) by focusing the attention on the identification of a global model that predicts the continuous outputs of the HDS. The proposed approach considers the identification of HDS in terms of the architectures and the learning algorithms developed for Feed-Forward neural networks.