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The Hammerstein and Wiener models are nonlinear representations od systems composed by the coupling of a static nonlinearity N and a linear system L in the form N-L (Hammerstein) and L-N (Wiener). Although the forms are very simple, these models still represent many real life processes such as mechanical systems, chemical processes, electrical and electronic systems, etc. The problem of identifying the static nonlinearity and linear system is a tough but interesting and important task, which 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 results of these researches have been useful and widely applied in automatic and control industry.
Our project in fact involves in a new technique that was recently proposed . This paper proposed a unified framework for the identification of both systems which are valid for single input single output (SISO) and multi inputs multi outputs (MIMO) systems, and without any particular structure for the static nonlinearity. This algorithm has been proven theoretically but it is necessary for such a verification of its characteristics compared with other existing algorithms.
The objective of this project is to discuss some practical aspects of implementation of this algorithm when applied to a simple example Hammerstein model. Then, this model is modified to represent a real life Wind Turbine Model . The identification technique is also modified accordingly, and numerical simulations are carried out to validate this technique. The project is open-ended and the may be further developed with the existence of noise and even some more complicated Hammerstein models.
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