Identification of the transfer function for dual-rate system based on IPSO

Authors:
Qi-Ting Gu;Wei-Xing Lin
Affiliations:
Faculty of Information Science and Technology, University of Ningbo, Ningbo, Zhejiang, China;Faculty of Information Science and Technology, University of Ningbo, Ningbo, Zhejiang, China
Venue:
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Year:
2009

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Abstract

This paper proposes that the dual-rate system is transformed from a lifted state-space model to the difference equation of transfer function. An improved particle swarm optimization (IPSO) algorithm is presented to estimate the transfer function's parameters. Comparing the simulation results with a recursive least squares (RLS) the algorithms of IPSO estimates parameters in different signal to noise ratio (SNR). Simulation results show that identification of IPSO has better stability and robust than one of RLS.