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PSO Assisted NURB Neural Network Identification

  • Xia Hong
  • Sheng Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7389)

Abstract

A system identification algorithm is introduced for Hammerstein systems that are modelled using a non-uniform rational B-spline (NURB) neural network. The proposed algorithm consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples are utilized to demonstrate the efficacy of the proposed approach.

Keywords

B-spline NURB neural networks De Boor algorithm Hammerstein model pole assignment controller particle swarm optimization system identification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xia Hong
    • 1
  • Sheng Chen
    • 2
    • 3
  1. 1.School of Systems EngineeringUniversity of ReadingUK
  2. 2.School of Electronics and Computer ScienceUniversity of SouthamptonUK
  3. 3.Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia

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