SIRMs fuzzy approximate reasoning using L-R fuzzy number as premise valuable

T. Mitsuishi, Takanori Terashima, Nami Shimada, Toshimichi Homma, Y. Shidama
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Abstract

This study has been studied SIRMs (Single Input Rule Modules) connected fuzzy inference model in order to provide the insight into fuzzy control systems. The framework consists of two propositions: To guarantee the convergence of optimal solution, a set of fuzzy membership functions (admissible fuzzy controller) which are selected out of continuous function space is compact metrizable. And assuming approximate reasoning to be a functional on the set of membership functions, its continuity is proved. Then, we show the existence of SIRMs which minimize (maximize) the integral performance function of the nonlinear feedback fuzzy system.
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以L-R模糊数为前提值的sims模糊近似推理
本文研究了单输入规则模块连接的模糊推理模型,以期对模糊控制系统提供更深入的认识。该框架由两个命题组成:为了保证最优解的收敛性,从连续函数空间中选取的一组模糊隶属函数(容许模糊控制器)是紧可度量的;并假设近似推理是隶属函数集上的泛函,证明了近似推理的连续性。然后,我们证明了非线性反馈模糊系统的积分性能函数的最小(最大)sirm的存在性。
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