Identification of Wiener models using optimal local linear models

The Wiener model is a versatile nonlinear block oriented model structure for miscellaneous applications. In this paper a method for identifying the parameters of such a model using optimal local linear models is presented. The linear model part is represented by a discretetime transfer function and the non-linear characteristic is represented by piece-wise linear functions. Parameter estimation as well as partitioning of the local linear models is simultaneously accomplished by the identification procedure. The optimality of the proposed algorithm is threefold: First, each local model is linear in the parameters and therefore optimal parameter estimation methods like Recursive Least-Squares can be applied, thus leading to a robust solution. Second, the region of validity of each local model is adaptively optimized using the Chi-squared distribution of the estimated residual. This approach not only enables an automatic choice of the model size but it also incorporates the measurement n...

• Type: Journal
• Year: 2008
• Where: SIMPRA
• Authors: Martin Kozek, Sabina Sinanovic
• Keywords: Linear Models, Local Linear Models, Model, SIMPRA 2008