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A Clustering Technique for the Identification of Piecewise Affine Systems


M. Muselli, D. Liberati, G. Ferrari-Trecate, M. Morari

International Workshop on Hybrid Systems: Computation and Control, Roma, Italy, pp. 218-231, March 28-30, A. Sangiovanni-Vincentelli, M. Di Benedetto (eds.), Lecture Notes in Computer Science 2034.

We propose a new technique for the identification of discrete-time hybrid systems in the Piece-Wise Affine (PWA) form. The identification algorithm proposed in (Ferrari-Trecate et al., 2000)is first considered and then improved under various aspects. Measures of confidence on the samples are introduced and exploited in order to improve the performance of both the clustering algorithm used for classifying the data and the final linear regression procedure. Moreover, clustering is performed in a suitably defined space that allows also to reconstruct different submodels that share the same coefficients but are defined on different regions.

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% Autogenerated BibTeX entry
@InProceedings { MusEtal:2001:IFA_543,
    author={M. Muselli and D. Liberati and G. Ferrari-Trecate and M. Morari},
    title={{A Clustering Technique for the Identification of Piecewise
	  Affine Systems}},
    booktitle={International Workshop on Hybrid Systems: Computation and
    address={Roma, Italy},
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