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Handling of inconsistent rules with an extended model of fuzzy reasoning

机译:用模糊推理的扩展模型处理不一致的规则

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摘要

It may not always be possible for an expert to provide a set of completely consistent rules. Even if the rules are consistent, all rules may not have equal importance to control the system. Moreover, for a fuzzy controller, the rule-base isusually tuned through modification of membership functions. Effect of changing a membership function is global in the sense that it influences all rules that involve the membership function. Here we propose a very effective extension of the conventionalfuzzy reasoning system with incorporation of an importance factor for each rule. This factor allows tuning of the system at the rule level. Of course, one can still tune the membership functions. It enables the system to cope with incorrect and/orincompatible rules and thereby enhances the robustness, flexibility and system modeling capability. The proposed model is quite general and can be used in different applications including control. In the present investigation, we demonstrate withextensive simulation how for a control application inconsistent rules can be dealt with.
机译:专家并非总是可能提供一组完全一致的规则。即使规则是一致的,所有规则对控制系统的重要性也可能不同。此外,对于模糊控制器,通常通过修改隶属函数来调整规则库。从某种意义上说,更改隶属函数的影响是全局性的,它会影响涉及该隶属函数的所有规则。在这里,我们提出了对传统模糊推理系统的非常有效的扩展,其中为每个规则引入了重要因素。该因素允许在规则级别调整系统。当然,仍然可以调整成员资格功能。它使系统能够处理不正确和/或不兼容的规则,从而增强了鲁棒性,灵活性和系统建模能力。所提出的模型非常通用,可以用于包括控制在内的不同应用。在本研究中,我们通过广泛的仿真演示了如何针对控制应用程序处理不一致的规则。

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