DocumentCode
702117
Title
Multi-scenario data driven fuzzy TSK nonholonomic mobile robot modelling
Author
Economou, J T ; Tsourdos, A ; Luk, P C K ; White, B A
Author_Institution
Department of Aerospace, Power and Sensors, CRANFIELD University-RMCS, Shrivenham, Wiltshire, Swindon, SN6 8LA, UK
fYear
2003
fDate
1-4 Sept. 2003
Firstpage
1857
Lastpage
1862
Abstract
In this paper the problem of multi-scenario data driven fuzzy parameter estimation is considered. Experimental data are used from a small scale differentially steered four-wheel mobile robot “PROMETHEUS”. In particular two key modes of operation were identified and the multi-model parameters were obtained using the subtractive clustering approach. The two modes of the mobile robot operation were blended using a suitable blending function. The robotic vehicle modes structure was of a 1-st order multivariate Takagi-Sugeno-Kang. The parameter estimation process also included a noncasual filtering approach which resulted in a reduced number of TSK rules.
Keywords
Clustering algorithms; Clustering methods; Data models; Fuzzy logic; Mathematical model; Mobile robots; Fuzzy logic; Takagi-Sugeno-Kang; mobile-robot; subtractive clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
European Control Conference (ECC), 2003
Conference_Location
Cambridge, UK
Print_ISBN
978-3-9524173-7-9
Type
conf
Filename
7085236
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