抄録
This paper deals with a quasi-ARX modeling approach to nonlinear black-box systems. A quasi-ARX model consists of two parts: The first part is a macro-model, which is a user-friendly interface constructed using application specific knowledge and the nature of network structure; The second part is an ordinary neurofuzzy network, which is used to parameterize the coefficients. A dimensionality reduction technique based on principal component analysis is introduced to improve the quasi-ARX modeling. The modeling and the parameter estimation are described in details. Numerical simulations are carried out to demonstrate the effectiveness of the proposed modeling approach.
