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

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 wi...

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Bibliographic Details
Published in2009 IEEE International Conference on Robotics and Biomimetics (ROBIO) pp. 1365 - 1371
Main Authors Qi-ting Gu, Wei-xing Lin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Difference equations
Dual-rate system
Improved Particle Swarm Optimization
Least squares approximation
Noise robustness
Parameter estimation
Parameters estimation
Particle swarm optimization
Recursive estimation
Recursive least squares
Resonance light scattering
Robust stability
Signal to noise ratio
Transfer function
Transfer functions
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Summary: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.
ISBN:9781424447749
1424447747
DOI:10.1109/ROBIO.2009.5420807