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Stochastic Fuzzy Control - Part II: Relationships Among a Priori Probabilities, Fuzzy Sets and Control Rules

机译:随机模糊控制 - 第二部分:先验概率,模糊集和控制规则之间的关系

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The role of the a priori probabilities is unclear for a stochastic fuzzy control with a single vector data in the first report, because in such a case the number of Gaussian potential functions is equal to the number of control rules. In addition, as in a conventional fuzzy control based on fuzzy reasoning, it is necessary to clarify the relationships between the fuzzy sets and the control rules. We here consider a static multiple model adaptive control (MMAC) for the initial data disribution, in which it is assumed that a single vector data is partitioned into two subvector data and the hierarchical hyprotheses are also introduced with respect to each initial data distribution. Then, two kinds of stochastic fuzzy controls are proposed on the basis of such a static MMAC: one case assigns the a priori probabilities to the fuzzy sets for each subvector data, and the other case assigns the a priori probabilities to the control rules.
机译:先验概率的作用对于第一报告中的单个矢量数据的随机模糊控制,因为在这种情况下,高斯潜在函数的数量等于控制规则的数量。 另外,如在基于模糊推理的传统模糊控制中,有必要阐明模糊集之间的关系和控制规则。 我们在此考虑用于初始数据的静态多模型自适应控制(MMAC),其中假设将单个向量数据被划分为两个子vector数据,并且还介绍了相对于每个初始数据分布的分层杂皮。 然后,在这种静态MMAC的基础上提出了两种随机模糊控制:一个案例将先验概率分配给每个子vector数据的模糊集,另一个案例为控制规则分配先验概率。

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