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

N. Yubazaki, J. Yi, M. Otani, K. Hirota
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引用次数: 12

Abstract

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.
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SIRM连通模糊推理模型及其在一阶滞后系统和二阶滞后系统中的应用
针对多输入模糊控制,提出了单输入规则模块连接模糊推理模型。该模型首先定义重要度,并对每个输入项构建单输入模糊规则模块。将各模块的重要度生成和模糊推理结果进行汇总,得到模型输出。所提出的模型只需要很少的规则和参数,而且规则的设计也容易得多。此外,每个输入项的作用可以根据专家的直觉经验,通过改变其重要程度来增强或减弱。将该模型应用于典型的一阶滞后系统和二阶滞后系统,验证了与传统模型相比,该模型在控制性能上的改进。
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Supporting rough set theory in very large databases using oracle RDBMS Theory of including degrees and its applications to uncertainty inferences Fuzzy decision making through relationships analysis between criteria Stratification structures on a kind of completely distributive lattices and their applications in theory of topological molecular lattices Supporting consensus reaching under fuzziness via ordered weighted averaging (OWA) operators
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