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Development and validation of the lane-keeping controller using a similarity-type fuzzy reasoning method

机译:基于相似型模糊推理方法的车道保持控制器开发与验证

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This paper proposes the Similarity-type Fuzzy Reasoning method based on the calculated overlap coefficient of sensor rules and sensor input data for a lane-keeping controller. Fuzzy control reasoned by a membership function and human-adjusted rules. Those are required to improve the control performance. In this paper, instead of using the membership function, the inference result was calculated by the similarity of the rules and the input data. We try to implement the lanekeeping controller using the similarity-type fuzzy reasoning method, and this method has been succeeded to develop new advance two-stage fuzzy control.
机译:提出了一种基于传感器规则的重叠系数和传感器输入数据的车道保持控制器相似度模糊推理方法。由隶属函数和人为调整的规则进行推理的模糊控制。这些都是提高控制性能所必需的。在本文中,不是使用隶属函数,而是通过规则和输入数据的相似性来计算推理结果。我们尝试使用相似型模糊推理方法来实现车道保持控制器,并且该方法已经成功开发了新的先进的两阶段模糊控制。

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