Design of a recursive parametric estimation algorithm for nonlinear system described by a Hammerstein mathematical model

Abstract

In this communication, a recursive parametric estimation algorithm is developed for the parametric estimation of nonlinear systems which can be described by a Hammerstein mathematical model. The formulation of this parametric estimation problem is made by using the method of the adjustable model and the least squares techniques. The stability analysis of the parametric estimation algorithm is made by using the Lyaponov theory. The performance of the developed recursive parametric estimation algorithm is illustrated using data from an experimental acid-base neutralization process.