Title :
Data-based generation of fuzzy rules for classification, prediction and control with the Fuzzy-ROSA method
Author :
Slawinski, T. ; Praczyk, J. ; Schwane, U. ; Krone, A. ; Kiendl, H.
Author_Institution :
Fac. of Electr. Eng., Univ. of Dortmund, Dortmund, Germany
fDate :
Aug. 31 1999-Sept. 3 1999
Abstract :
This paper presents three applications of the Füzzy-ROSA method. The first application, the classification of automatic gear boxes by 149 characteristics, is an example of data-based rule generation and complexity reduction in high-dimensional search spaces. The second application is an example of the use of very noisy and contradictory data where the cancellation behaviour of insurance clients is predicted on the basis of sociodemographic characteristics. In the third application a generated fuzzy model is used to adapt the parameters of the position controller of an industrial robot to optimize the continuous path accuracy. This application demonstrates the process of learning from good and poor control strategies.
Keywords :
control system synthesis; fuzzy control; industrial robots; knowledge based systems; pattern classification; position control; search problems; complexity reduction; continuous path accuracy optimization; data-based rule generation; fuzzy classifier; fuzzy rules; fuzzy-ROSA method; generated fuzzy model; high dimensional search space; industrial robot; learning process; position controller; sociodemographic characteristics; Adaptation models; Aerospace electronics; Contracts; Input variables; Insurance; Pragmatics; Robots; Complexity Reduction; Computational Intelligence; Data-based Modelling; Fuzzy-Logic; Fuzzy-ROSA method;
Conference_Titel :
Control Conference (ECC), 1999 European
Conference_Location :
Karlsruhe
Print_ISBN :
978-3-9524173-5-5