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Parameter Identification and Simulation of The Noise-involved Hysteretic Model Using Improved Genetic Algorithm

机译:改进遗传算法的噪声滞回模型参数辨识与仿真

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Hysteresis is a specific character of a wide range of physical systems and devices, such as electromagnetic fields,mechanical stress-strain elements, and electronic relay circuits. The extended Bouc-Wen model is one of the most widely accepted phenomenologicai models of hysteresis in mechanics. However the multi parameters have plagued its further application because the capability of computer and algorithm available currently can not meet the need completely. Thus to exploit an efficient and accurate parallel algorithm is very essential and significant. This paper is committed to propose an improved genetic algorithm(GA) so as to identify the parameter of the Bouc-Wen model effectively. Finally a large amount of noise-involved data is employed to verify the proposed approach is very effective and accurate.
机译:磁滞是各种物理系统和设备的特定特征,例如电磁场,机械应力应变元件和电子继电器电路。扩展的Bouc-Wen模型是力学中滞后现象最广泛接受的现象学模型之一。然而,由于当前可用的计算机和算法的能力不能完全满足需求,因此多参数困扰了其进一步的应用。因此,开发一种高效,准确的并行算法是非常必要和重要的。本文致力于提出一种改进的遗传算法(GA),以有效地识别Bouc-Wen模型的参数。最后,大量涉及噪声的数据被用来验证所提出的方法是非常有效和准确的。

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