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

Haichen Guo, Boyan Zhou, Pingping Yang, Xincheng Gu
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引用次数: 8

Abstract

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.
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改进Stribeck模型和模拟退火遗传算法在摩擦参数辨识中的应用
摩擦在物理环境中是相当普遍和不可避免的。在摩擦过程中,振动和碰撞会给识别结果带来较大的偏差。本文实现了受振动和碰撞影响的摩擦过程以及数据采集。在摩擦模型方面,根据傅立叶级数理论,在摩擦模型中引入正弦滤波项,消除振动和碰撞对参数辨识的影响。为了得到更准确、更高效的识别算法,我们将模拟退火算子嵌入到遗传算法中,充分利用遗传算法和模拟退火算法的优点。混合算法可以有效地确定振动和碰撞影响下的摩擦过程识别结果。
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