An iterative parametric estimation method for Hammerstein large-scale systems: a simulation study of hydraulic process. (2016) - Elloumi, Mourad; Kamoun, Samira
This paper aims at developing an iterative method which permits to estimate the parameters of single-input single-output (SISO) large-scale nonlinear systems, described by Hammerstein mathematical models. We particularly focus on the dynamic large-scale nonlinear systems, which are made up of several interconnected nonlinear monovariable subsystems. Each subsystem can operate in a stochastic environment and be described by a discrete-time Hammerstein mathematical model with known structure variables (order, delay) and unknown time-varying parameters. The problem formulation is achieved based on the prediction error method and the least-squares techniques. The convergence analysis of the recursive algorithm is provided using the differential equation approach and its performance is illustrated by treating two simulation examples.