Identification of nonlinear dynamic systems described by Hammerstein state-space models with discontinuous nonlinearities. (2017)

• Record Type: Journal Article
• Authors: Salhi, Houda; Kamoun, Samira
• Is Part Of: International journal of engineering systems modelling and simulation. Volume 9:Number 3(2017)
• Page Start: 127
• Page End: 135
• Publication Date: 2017
• Subjects: recursive algorithm -- parameter estimation -- state estimation -- Hammerstein model -- discontinuous nonlinearities -- adjustable model -- least squares technique -- Kalman filter -- preaload -- dead zone nonlinearity; Engineering systems -- Computer simulation -- Periodicals; Engineering systems -- Mathematical models -- Periodicals; 620.0042
• Languages: English
• ISSNs: 1755-9758

Abstract

This paper deals with the parameter estimation problem of Hammerstein state-space models with different nonlinearities. The basic idea is to develop a recursive algorithm which estimate jointly the system model parameters and the state variables by combining the adjustable model method, the least squares technique and the Kalman filter. A numerical example is provided to test the flexibility and the effectiveness of the proposed algorithm.