Identification of PWA models via optimal data compression

In this paper, a new identification method for non-parametric piecewise affine (PWA) models is introduced. The method is based on the non-parametric data-based representation of PWA maps and the data compression with l1 optimization technique, which enable the method to deal with large data sets. In the proposed scheme, the prior knowledge about partitioning of the PWA map is not required, and the trade-off between complexity and accuracy of the model is easily adjusted by one parameter, which can be determined by holdout validation technique in practical situations. These features of the proposed method provide the high usability in practical problems, which is demonstrated through numerical and experimental examples.