Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/8091
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Title: | Recursive bayesian identification of nonlinear autonomous systems |
Authors: | Simão, Tiago Barão, Miguel Marques, Jorge S. |
Issue Date: | Jul-2012 |
Citation: | T. Simão, M. Barão, J. S. Marques, "Recursive bayesian identification of nonlinear autonomous systems", in proceedings of 20th Mediterranean Conference on Control and Automation, pp. 210-215, Barcelon, Spain, July, 2012. |
Abstract: | This paper concerns the recursive identification of nonlinear discrete-time systems for which the original equations of motion are not known. Since the true model structure is not available, we replace it with a generic nonlinear model. This generic model discretizes the state space into a finite grid and associates a set of velocity vectors to the nodes of the grid. The velocity vectors are then interpolated to define a vector field on the complete state space. The proposed method follows a Bayesian framework where the identified velocity vectors are selected by the maximum a posteriori (MAP) criterion. The resulting algorithms allow a recursive update of the velocity vectors as new data is obtained. Simulation examples using the recursive algorithm are presented. |
URI: | http://hdl.handle.net/10174/8091 |
Type: | article |
Appears in Collections: | INF - Artigos em Livros de Actas/Proceedings
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