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|Title: ||Recursive bayesian identification of nonlinear autonomous systems|
|Authors: ||Simão, Tiago|
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.|
|Appears in Collections:||INF - Artigos em Livros de Actas/Proceedings|
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