Nonlinear system identification using radial basis functions
Focussing on applications to fluid flow phenomena, we are interested in developing dynamical system models that are based on the discrete multivariate time series information only. A method based on radial basis functions and linear multi-step methods is used to construct continuous nonlinear models that approximate the original dynamical system. Information, such as the structure of the original system, is incorporated into the models through weak constraints. The formulation of the model and its advantages associated with modeling is described. Different examples are presented that highlight the various characteristics of the model and its effectiveness in dealing with various problems encountered in fluid flow problems. Copyright (C) 2009 John Wiley & Sons, Ltd.
radial basis functions nonlinear dynamical systems time series analysis time series prediction navier-stokes equations turbulence proper orthogonal decomposition