In this paper a new system identification algorithm is introduced for Hammerstein systems based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a non-uniform rational B-spline (NURB) neural network. The proposed system identification algorithm for this NURB network based Hammerstein system consists of two successive stages. First the...

In this paper a dynamic behavior model of analog to digital converters is proposed. The model is aimed for post correction in wideband applications. The suggested post correction method is a combination of look up tables and model based correction. The model consists of three components. The first is a component represented by a Hammerstein model; that is a static nonlinearity followed by a tim...

The identification difficulties for a dual-rate Hammerstein system lie in two aspects. First, the identification model of the system contains the products of the parameters of the nonlinear block and the linear block, and a standard least squares method cannot be directly applied to the model; second, the traditional single-rate discrete-time Hammerstein model cannot be used as the identificati...

This article studies the subspace identification methods (SIMs) for Hammerstein systems with major focus on a rank constraint and the related dimension problem. We analyse the effects of the rank constraint on the three steps of a unifying framework for SIMs: the rank constraint has no effect on the first two steps, but does so on the third step. If the rank constraint is ignored, as in the exi...

InterSymbol Interference (ISI) of the radio propagation through channels is a major factor that limits the performance of mobile communication systems and can be compensated by equalization. One of the basic groups of equalizers is based on linear algorithms. In this paper, we propose the other method based on Hammerstein filter as a nonlinear memoryless blind equalizer. We have compared these ...

In this paper, a new nonlinear discrete-time PID is proposed to control Hammerstein model. This model is composed by a static nonlinearity gain associated to a linear dynamic subsystem. Nonlinear polynomial structures are used to identify and to control this class of systems. The determination of parameters is based on the use of RLS algorithm. A coupled two-tank process is given to illustrate ...

Derived from the idea of stochastic approximation, recursive algorithms to identify a Hammerstein system are presented. Two of them recover the characteristic of the nonlinear memoryless subsystem while the third one estimates the impulse response of the linear dynamic part. The a priori information about both subsystems is nonparametric. Consistency in quadratic mean is shown and the convergen...

This paper uses the key-term separation principle and develops a multi-innovation stochastic gradient algorithm for Hammerstein MIMO output error systems. The basic idea is to decompose a Hammerstein MIMO system into two subsystems and to identify the parameters of each subsystem interactively. The parameter estimation accuracy can be improved with the innovation length increasing. The simulati...

We numerically investigate the sense in which an adaptive control law achieves internal model control of Hammerstein plants with Prandtl–Ishlinskii hysteresis. We apply retrospective cost adaptive control to a command-following problem for uncertain Hammerstein systems with hysteretic input nonlinearities. The only required modeling information of the linear plant is a single Markov parameter. ...

This paper deals with modeling and parameter identification of nonlinear systems described by Hammerstein model having Piecewise nonlinear characteristics such as Dead-zone nonlinearity characteristic. The simultaneous use of both an easy decomposition technique and the triangular basis functions leads to a particular form of Hammerstein model. The approximation by using Triangular basis functi...