System identification of a class of Wiener systems with hysteretic nonlinearities. (15th July 2016)

• Record Type: Journal Article
• Authors: Radouane, Abdelhadi; Giri, Fouad; Ikhouane, Faycal; Ahmed‐Ali, Tarek; Chaoui, Fatima‐Zahra; Brouri, Adil
• Is Part Of: International journal of adaptive control and signal processing. Volume 31:Number 3(2017)
• Page Start: 332
• Page End: 359
• Publication Date: 2016-07-15
• Subjects: system identification -- Wiener systems -- frequency identification; Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.2700
• Languages: English
• ISSNs: 0890-6327

Abstract

Summary: Existing works on Wiener system identification have essentially been focused on the case where the output nonlinearity is memoryless. When memory nonlinearities have been considered, the focus has been restricted to backlash like nonlinearities. In this paper, we are considering Wiener systems where the output nonlinearity is a general hysteresis operator captured by the well‐known Bouc–Wen model. The Wiener system identification problem is addressed by making use of a steady‐state property, obtained in periodic regime, referred to as 'hysteretic loop assumption'. The complexity of this problem comes from the system nonlinearity as well as its unknown parameters that enter in a non‐affine way in the model. It is shown that the linear part of the system is accurately identified using a frequency method. Then, the nonlinear hysteretic subsystem is identified, on the basis of a parameterized representation, using a prediction‐error approach. Copyright © 2016 John Wiley & Sons, Ltd.