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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.
Type: article
Appears in Collections:INF - Artigos em Livros de Actas/Proceedings

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