DocumentCode :
684983
Title :
Kalman smoother and weighted fusion algorithm for fractional systems
Author :
Xiaojun Sun ; Guangming Yan ; Bo Zhang
Author_Institution :
Dept. of Autom., Heilongjiang Univ., Harbin, China
Volume :
01
fYear :
2013
fDate :
16-18 Aug. 2013
Firstpage :
151
Lastpage :
158
Abstract :
For the linear discrete fractional state-space systems, a fractional Kalman smoother is presented in this paper. The detail derivation is given. For the multisensor linear discrete fractional state-space systems, a weighted measurement fusion algorithm is presented based on the linear minimum variance optimal fusion rules. It is rigorously proved that the weighted measurement fusion fractional Kalman smoother is numerically identical to the centralized fusion fractional Kalman smoother, so that it has the global optimality. Its effectiveness is shown by a simulation example.
Keywords :
discrete systems; linear systems; optimal control; sensor fusion; state-space methods; Kalman smoother algorithm; centralized fusion fractional Kalman smoother; fractional systems; global optimality; linear minimum variance optimal fusion rules; multisensor linear discrete fractional state-space systems; weighted fusion algorithm; weighted measurement fusion algorithm; weighted measurement fusion fractional Kalman smoother; Robots; Weight measurement; discrete fractional state-space systems; fractional Kalman filter; information fusion; weighted measurement fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measurement, Information and Control (ICMIC), 2013 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-1390-9
Type :
conf
DOI :
10.1109/MIC.2013.6757936
Filename :
6757936
Link To Document :
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