Kernel manifold regression for the coupled electric drives dataset

M. Mazzoleni, M. Scandella, F. Previdi

The aim of this work is to introduce the concept of manifold regularization to the identification of dynamic systems. The method has been tested on the coupled electric drives problem, using a purely black box approach in the framework of the Reproducing Kernel Hilbert Spaces (RKHS). [Code]

NOTE: If you plan to use the provided code, please cite the following papers:

  • M. Mazzoleni, S. Formentin, M. Scandella, F. Previdi «Semi-supervised learning of dynamical systems: a preliminary study.» 16th European Control Conference (ECC), Limassol, Cyprus, 2018. In press
  • M. Mazzoleni, M. Scandella, S. Formentin, F. Previdi «Identification of nonlinear dynamical system with synthetic data: a preliminary investigation.» 18th IFAC Symposium on System Identification, Stockholm, Sweden, 2018. In press
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