Identification of ARX Hammerstein Models based on Twin Support Vector Machine Regression

Abstract

In this paper we develop a new algorithm to identify Auto-Regressive Exogenous (ARX) input Hammerstein Models based on Twin Support Vector Machine Regression (TSVR). The model is determined by minimizing two ε-insensitive loss functions. One of them determines the ε1-insensitive down bound regressor while the other determines the ε1-insensitive up bound regressor. The algorithm is compared to Support Vector Machine (SVM) and Least Square Support Vector Machine (LSSVM) based algorithms using simulation.