A switching detection method based on projected subspace classification

In this paper an innovative switching detection method for piecewise linear systems is presented. The principle used for switching detection is based on finding projected subspaces from batches of input-output data, which are taken from the full data set. The method runs off-line, incrementally over all the data and, at each time, a different batch is used to compute the projected subspace. In this way, the segmentation and classification of data are entirely based on the information retrieved from the projected subspace, i.e. the subspace dimension and basis. The output of the method is a matrix of weights that assigns each pair of input-output measured data to the respective local system. Simulation experiments show the effectiveness of the proposed approach.