Abstract
A new type of rough fuzzy controller and its design method are presented and show how the rough logic is combined with fuzzy inference. In this approach, rough set theory is used to derive the minimal set of rules from input output data, and by complementing the information of output control corresponding to the rough reduced rules, a T-S type of rough fuzzy control system is constructed, which can solve the problem that the number of rules in a fuzzy controller increases exponentially with the number of variables involved.
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© 2003 Springer-Verlag Berlin Heidelberg
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Huang, J., Li, S., Man, C. (2003). A T-S Type of Rough Fuzzy Control System and Its Implementation. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_49
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DOI: https://doi.org/10.1007/3-540-39205-X_49
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