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Neuro-fuzzy Hysteresis Modeling of Magnetorheological Dampers

机译:磁流变阻尼器的神经模糊滞后模型

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This paper presents the neuro-fuzzy modeling approach to analyze the test results of MR damper. Every Electric current in provides to MR Fluid will have a different output. On the other hand, the meandering type valve has a different output and calculation. Therefore, the prototype of MR Damper that has been made was taken to a laboratory to test using Dynamic Testing Machine. The data test result will be analyzed using Neuro-Fuzzy. This paper aims to find a correlation between every variable is there in the testing of MR Damper. For the hysteresis modeling purpose, some parts of the data are taken as the training data source for the optimization parameters in the Neuro-Fuzzy model. The performance of the trained Neuro-Fuzzy model is assessed by validating the model output with the remaining measurement data and benchmarking. The assigned membership function results in a minimum error of 0.16 from 3000 epoch from 3 sets of data given as training data.
机译:本文介绍了神经模糊建模方法,分析了阻尼器MR Damper的测试结果。 向MR流体提供的每个电流都有不同的输出。 另一方面,蜿蜒的阀门具有不同的输出和计算。 因此,已经制作的Damper MR Damper的原型被带到了实验室使用动态测试机器进行测试。 使用神经模糊将分析数据测试结果。 本文旨在找到每个变量之间的相关性在测试MR Damper的测试中。 对于滞后建模目的,数据的某些部分被视为神经模糊模型中优化参数的训练数据源。 通过使用剩余的测量数据和基准测试来评估培训的神经模糊模型的性能。 指定的隶属函数从3套数据中的3000时计量为0.16的最小误差。

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