SIRM's connected fuzzy inference model and its applications to first-order lag systems and second-order lag systems

SIRMs (Single Input Rule Modules) Connected Fuzzy inference Model is proposed for multiple input fuzzy control. In the model, the importance degree is defined first and single input fuzzy rule module is constructed for each input item. The model output is obtained by summarizing the production of th...

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Bibliographic Details
Main Authors: Yubazaki, N., Yi, J., Otani, M., Hirota, K.
Format: Conference Proceeding
Language:English
Subjects:
Fuzzy systems
System performance
Online Access:Request full text
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Summary:SIRMs (Single Input Rule Modules) Connected Fuzzy inference Model is proposed for multiple input fuzzy control. In the model, the importance degree is defined first and single input fuzzy rule module is constructed for each input item. The model output is obtained by summarizing the production of the importance degree and the fuzzy inference result of each module. The proposed model needs both very few rules and parameters and the rules can be designed much easier. Moreover, the role of each input item can be strengthened or weakened by changing its importance degree according to experts' intuitive experiences. The proposed model is applied to typical first order lag systems and second order lag systems to confirm the improvement in control performance compared with the conventional model.
DOI:10.1109/AFSS.1996.583707