An iterative parametric estimation method for Hammerstein large-scale systems: a simulation study of hydraulic process. (2016)

• Record Type: Journal Article
• Authors: Elloumi, Mourad; Kamoun, Samira
• Is Part Of: International journal of simulation and process modelling. Volume 11:Number 3/4(2016)
• Page Start: 207
• Page End: 219
• Publication Date: 2016
• Subjects: large-scale nonlinear systems -- stochastic systems -- mathematical modelling -- Hammerstein models -- parametric estimation -- convergence analysis -- simulation -- hydraulic processes -- hydraulics -- single-input single-output -- SISO systems; Management -- Computer simulation -- Periodicals; Mathematical models -- Periodicals; Operations research -- Periodicals; Simulation methods -- Periodicals; 003.05
• Languages: English
• ISSNs: 1740-2123

Abstract

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.