A unified approach for the identification of SISO/MIMO Wiener and Hammerstein systems

Hammerstein and Wiener models are nonlinear representations of systems composed by the coupling of a static nonlinearity N and a linear system L in the form N-L and L-N respectively. These models can represent real processes which made them popular in the last decades. The problem of identifying the static nonlinearity and linear system is not a trivial task, and has attracted a lot of research interest. It has been studied in the available literature either for Hammerstein or Wiener systems, and either in a discrete-time or continuous-time setting. The objective of this paper is to present a uni ed framework for the identification of these systems that is valid for SISO and MIMO systems, discrete and continuous-time setting, and with the only a priori knowledge that the system is either Wiener or Hammerstein.Preprin

Frequency identification of Wiener systems with Backlash operators using separable least squares estimators

This paper deals with the identification of Wiener models that involve backlash operators bordered by possibly noninvertible parametric lines. The latter are also allowed to cross each other making possible to account for general-shape static nonlinearities. The linear dynamic subsystem is not-necessarily parametric but is BIBO stable. A frequency identification method is developed that provides estimates of the nonlinear operator parameters as well as estimates of the linear subsystem frequency gain. The method involves standard and separable least squares estimators that all are shown to be consistent. Backlash operators and memoryless nonlinearities are handled within a unified framework.Preprin

Identification of hammerstein-wiener systems including backlash input nonlinearities

Postprint (published version

Viscous plus Dahl model for MR damper characterization: A real-time hybrid test (RTHT) validation

Magnetorheological dampers have raised as promising devices for structural seismic protection since they have many attractive features such as small power requirements, reliability, and relatively low cost. These devices have strongly nonlinear behaviour which is very difficult to characterize. For this reason, the modelling of MR dampers has been an active field during the last years and has produced several models by combining a physical insight with a black-box approach. Among them, the so called “viscous + Dahl model” has been introduced as a particular case of the normalized version of the Bouc-Wen. Viscous + Dahl model is indeed significantly simpler than some other approaches and has well established conditions to ensure its physical and mathematical consistency. This work deals with the modelling and identification of a small scale MR damper which is described by the viscous + Dahl model. The obtained model is validated experimentally into a real time hybrid test (RTHT) configuration where the MR damper is working as the seismic protection of a civil structure. The results show a good match between experimental and predicted forces

System identification of a class of Wiener systems with hysteretic nonlinearities

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.Postprint (author's final draft

A unified approach for the identification of SISO/MIMO Wiener and Hammerstein systems

Hammerstein and Wiener models are nonlinear representations of systems composed by the coupling of a static nonlinearity N and a linear system L in the form N-L and L-N respectively. These models can represent real processes which made them popular in the last decades. The problem of identifying the static nonlinearity and linear system is not a trivial task, and has attracted a lot of research interest. It has been studied in the available literature either for Hammerstein or Wiener systems, and either in a discrete-time or continuous-time setting. The objective of this paper is to present a uni ed framework for the identification of these systems that is valid for SISO and MIMO systems, discrete and continuous-time setting, and with the only a priori knowledge that the system is either Wiener or Hammerstein