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Nelles, O. (2001) Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models. Springer, New York. http://dx.doi.org/10.1007/978-3-662-04323-3

has been cited by the following article:

• TITLE: Dynamic Programming to Identification Problems

  AUTHORS: Nina N. Subbotina, Evgeniy A. Krupennikov

  KEYWORDS: Nonlinear System, Optimal Control, Identification, Discrepancy, Dynamic Programming

  JOURNAL NAME: World Journal of Engineering and Technology, Vol.4 No.3D, October 29, 2016

  ABSTRACT: An identification problem is considered as inaccurate measurements of dynamics on a time interval are given. The model has the form of ordinary differential equations which are linear with respect to unknown parameters. A new approach is presented to solve the identification problem in the framework of the optimal control theory. A numerical algorithm based on the dynamic programming method is suggested to identify the unknown parameters. Results of simulations are exposed.