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Self-organizing Fuzzy Controller Based on Fuzzy Neural Network

机译:基于模糊神经网络的自组织模糊控制器

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摘要

Fuzzy logic has been successfully used for nonlinear control systems. However, when the plant is complex or expert knowledge is not available, it is difficult to construct the rule bases of fuzzy systems. In this paper, we propose a new method of how to construct automatically the rule bases using fuzzy neural network. Whereas the conventional methods need the training data representing input-output relationship, the proposed algorithm utilizes the gradient of the performance index for the construction of fuzzy rules and the tuning of membership functions. Experimental results with the inverted pendulum show the superiority of the proposed method in comparison to the conventional fuzzy controller.
机译:模糊逻辑已成功用于非线性控制系统。但是,当工厂复杂或没有专家知识时,很难构建模糊系统的规则库。本文提出了一种利用模糊神经网络自动构建规则库的新方法。常规方法需要训练数据来表示输入输出关系,而该算法利用性能指标的梯度来构建模糊规则和隶属函数的调整。与传统的模糊控制器相比,倒立摆的实验结果表明了该方法的优越性。

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