A neural-fuzzy controller with heterogeneous neurons

Chih-Chi Chang, Chungyong Tsai
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Abstract

For engineering applications, complex pre-calculations may be necessary to evaluate the fuzzy degree of a simple linguistic term in the conditional part. If these pre-calculations are excluded from the system, it is difficult to discriminate the physical meaning of the rule from the neural nets. Therefore, this work applies feature extraction to replace these pre-calculations. The proposed neural fuzzy system extracts features by heterogeneous neurons. The proposed system's structure and its advantages are described in detailed. A controller designed by the proposed neural fuzzy system is presented as well.
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具有异质神经元的神经模糊控制器
对于工程应用,复杂的预计算可能是必要的,以评估一个简单的语言术语在条件部分的模糊程度。如果将这些预计算排除在系统之外,则很难从神经网络中区分规则的物理含义。因此,本工作采用特征提取来代替这些预计算。所提出的神经模糊系统通过异质神经元提取特征。详细介绍了该系统的结构和优点。并给出了利用该神经模糊系统设计的控制器。
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