Title: An iterative parametric estimation method for Hammerstein large-scale systems: a simulation study of hydraulic process
Authors: Mourad Elloumi; Samira Kamoun
Addresses: Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA), National School of Engineering of Sfax, University of Sfax, Postal Box 1173, 3038 Sfax, Tunisia ' Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA), National School of Engineering of Sfax, University of Sfax, Postal Box 1173, 3038 Sfax, Tunisia
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.
Keywords: large-scale nonlinear systems; stochastic systems; mathematical modelling; Hammerstein models; parametric estimation; convergence analysis; simulation; hydraulic processes; hydraulics; single-input single-output; SISO systems.
International Journal of Simulation and Process Modelling, 2016 Vol.11 No.3/4, pp.207 - 219
Available online: 19 Aug 2016 *Full-text access for editors Access for subscribers Purchase this article Comment on this article