Neurofuzzy state identification using prefiltering


Hong, X., Harris, C.J. and Wilson, P.A. (1999) Neurofuzzy state identification using prefiltering. Control Theory and Applications, IEE Proceedings, 146, (2), 234-240. (doi: 10.1049/ip-cta:19990121).

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Original Publication URL: http://dx.doi.org/10.1049/ip-cta:19990121

Description/Abstract

A new state estimator algorithm is introduced based on a neurofuzzy network and the Kalman filter algorithm. The major contribution of the paper is recognition of a bias problem in the parameter estimation of the state space model and the introduction of a simple ffective pre-filtering method to achieve unbiased parameter estimates in the state space model which will then be applied for state estimation using the Kalman filtering algorithm. Fundamental to this method is a simple pre-filtering procedure using a non-linear principal component analysis PCAmethod based on the neuro-fuzzy basis set. This preltering procedure can be performed withoutprior system structure information. Some numerical examples are included to demonstrate theeffectiveness of the new approach.

Item Type: Article
ISSNs: 1350-2379 (print)
Related URLs:
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions: University Structure - Pre August 2011 > School of Engineering Sciences > Fluid-Structure Interactions
ePrint ID: 50946
Date Deposited: 23 Apr 2008
Last Modified: 27 Mar 2014 18:34
URI: http://eprints.soton.ac.uk/id/eprint/50946

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