基于自适应神经元学习模糊控制规则

Learning Fuzzy Control Rules Using Adaptive Neural Element

本文给出了利用自适应神经元学习、修改模糊控制规则的新方法。该方法可以学习与当前控制过程输出性能有关的在过去起作用的控制规则，可以随过程环境变化自动调整控制规则，以改善过程输出性能。

This paper proposes a new method to learn fuzzy control rules using adaptive neural element. Based on the learning algorithm of adaptive neural element, the method presented in the paper can generate and modify control rules which act on process previously and affect the current performance of control system.For the convenience of learning control rules , the paper adopts a fuzzy logic controller composed of control rules expressed by reference fuzzy sets and corresponding approximate reasoning.