Abstract
In this paper we present a novel procedure for the identification of hybrid systems in the piece-wise ARX form. The procedure consists of three steps: 1) parameter estimation, 2) classification of data points and 3) partition estimation. Our approach to parameter estimation is based on the gradual refinement of the a-priori information about the parameter values, using the Bayesian inference rule. Particle filters are used for a numerical implementation of the proposed parameter estimation procedure. Data points are subsequently classified to the mode which is most likely to have generated them. A modified version of the multi-category robust linear programming (MRLP) classification procedure, adjusted to use the information derived in the previous steps of the identification algorithm, is used for estimating the partition of the PWARX map. The proposed procedure is applied for the identification of the component placement process in pick-and-place machines.
Original language | English |
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Title of host publication | 43rd IEEE Conference on Decision and Control |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 13-19 |
Number of pages | 7 |
Volume | 1 |
Publication status | Published - 1 Dec 2004 |
Event | 43rd IEEE Conference on Decision and Control (CDC 2004) - "Atlantis", Nassau, Bahamas Duration: 14 Dec 2004 → 17 Dec 2004 Conference number: 43 http://cdc2004.ieeecss.org/ |
Conference
Conference | 43rd IEEE Conference on Decision and Control (CDC 2004) |
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Abbreviated title | CDC 2004 |
Country/Territory | Bahamas |
City | Nassau |
Period | 14/12/04 → 17/12/04 |
Internet address |