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Application of modified Stribeck model and simulated annealing genetic algorithm in friction parameter identification

机译:改进的Stribeck模型和模拟退火遗传算法在摩擦参数识别中的应用

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Friction is quite common and inevitable in physical environments. During the process of friction, vibration and collision will bring large deviations to identification results. In this paper, friction process with the influence of vibration and collision as well as data collection are implemented. In terms of friction model, according to the theory of Fourier series, we can introduce sine filter terms into friction model to eliminate influence of vibration and collision on parameter identifications. To get a much more accurate and efficient algorithm of identification, we embed simulated annealing operator into a genetic algorithm to take the advantages of both genetic algorithm and simulated annealing algorithm. With the hybrid algorithm, the identification results of friction process under the influence of the vibration and collision can be determined effectively.
机译:在物理环境中,摩擦非常普遍且不可避免。在摩擦,振动和碰撞过程中,识别结果会有较大偏差。本文实现了受振动和碰撞影响的摩擦过程以及数据收集。在摩擦模型方面,根据傅立叶级数理论,我们可以将正弦滤波器项引入摩擦模型中,以消除振动和碰撞对参数识别的影响。为了获得更准确,更有效的识别算法,我们将模拟退火算子嵌入遗传算法中,以充分利用遗传算法和模拟退火算法的优势。利用混合算法,可以有效地确定在振动和碰撞影响下的摩擦过程识别结果。

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