An improved fuzzy inference algorithm by weighted in fuzzy controller

A conventional fuzzy control system has some problems in compositional rule of inference. Therefore, it produces a big error for a premise which is very similar or identical to one of premises in rules. It is because the importance of rules is not taken into the consideration for inference. To overcome of the problem, we propose an improved fuzzy inference algorithm to reduce the error by providing weights to composition of rules according to the similarity of premises. We show that the proposed similarity measure can reduce a lot of error regions compared with the conventional fuzzy inference method using the example of a fuzzy controller.