Research on Identification for a Class of Dynamic System

  • Xiaoping Xu
  • Yuan Yin
  • Feng Wang
  • Fucai Qian
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 146)


Because nonlinear dynamic systems are various, they are still not well solved via the traditional identification methods. This paper supposes that an original dynamic system is described by Hammerstein model initially. Its transfer function can then be changed into a simple form via expansion, thus generating an intermediate model and its parameters are obtained by an impoved particle swarm optimization. Finally, the parameters are gotten by the corresponding parameters’ relationships. Accordingly, the original system is identified. To demonstrate the feasibility of the proposed method, illustrative examples are included.


System identification Hammerstein model Evolutionary algorithm 


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of SciencesXi’an University of TechnologyXi’anChina
  2. 2.School of SciencesXi’an Jiaotong UniversityXi’anChina

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