Abstract
Many control systems have been changed from manual controls to automatic controls. Fuzzy control has played an important role in these changes. However, because knowledge is gained through everyday working experience and intiution, it is difficult for experts(control operators)to describe their own knowledge and skills in linguistic terms. Yet this linguistic description is still a necessary step in the construction of fuzzy control ruled. One solution to this problem is inductive learning and many algorithms have been developed to extraxt or generate rules from operator data. ID3, a very famous inductive learning algorithm, is an easy and powerful algorithm. It can make small and useful decision trees. But unfortunately, it cannot deal with real numbers such as control data. It can only deal with attributes and classes. There are some papers on fuzzy ID3, which can deal with fuzzy number attributes. However, there are no reports about a version of ID3 which can deal with classes in real numbers. In this paper, we propose a new fuzzy ID3 which can deal with fuzzy classes given in real numbers. This new fuzzy ID3 uses a fuzzy clustering algorithm FCM to deal with the real numbers. Next, We apply it to input/output data obtained from behavior of experts in the inverted pendulum control and extracted fuzzy control rules from the data. Finally, we show simulation results of the inverted pendulum control by the fuzzy rules and discuss the performance of the results.
