Parameter Identification of a Nonlinear Two Mass System Using Prior Knowledge

Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 68)

Abstract

This article presents a new method for system identification based on dynamic neural networks using prior knowledge. A discrete chart is derived from a given signal flow chart. This discrete chart is implemented in a dynamic neural network model. The weights of the model correspond to physical parameters of the real system. Nonlinear parts of the signal flow chart are represented by nonlinear subparts of the neural network. An optimization algorithm trains the weights of the dynamic neural network model. The proposed identification approach is tested with a nonlinear two mass system.

Keywords

System identification two mass system dynamic neural network Levenberg-Marquardt 

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Institute for Electrical Drive SystemsTechnical University of MunichMünchenGermany

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