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State estimation of nonlinear system through Particle Filter based Recurrent Neural Networks

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4 Author(s)
N. Yadaiah ; Department of Electrical and Electronics Engineering, JNTUH College of Engineering, Hyderabad, Andhra Pradesh, INDIA ; Raju S. Bapi ; A. Suresh Kumar ; M. Roopchandan

This paper presents a Hybrid Particle Filter based RNN method for state estimation of non-linear dynamical system with knowledge of its input and output measurements. Particle filters are sequential Monte Carlo methods based on point mass (or particle) representations of probability densities, which is used to train Recurrent Neural Networks for estimation problems. The performance this method is compared with EKF based estimation and RNN based estimation. An Induction motor is considered as typical non-linear system and is implemented in MATLAB environment.

Published in:

Recent Advances in Intelligent Computational Systems (RAICS), 2011 IEEE

Date of Conference:

22-24 Sept. 2011