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December 6, 2025Journal of Computational and Nonlinear Dynamics0 citations

Development of a Two-Mass Dual LuGre Model for Nonlinear Dynamics in Feed Drive System

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ZJZheng-Wei JianTZTing-hua ZhangMTMeng Shiun Tsai

Key Points

  • The model accurately simulates dynamic characteristics during velocity reversal, yielding important insights.
  • Experimental validation indicates a maximum tracking error of about 3.7%, demonstrating model effectiveness against real-world scenarios.
  • Utilization of LuGre friction models allows for detailed simulation of frictional effects in system dynamics.
  • The approach emphasizes understanding the relationship between backlash and system dynamics during operation disruptions.

Abstract

Abstract This study presents an innovative transmission model to investigate the nonlinear dynamic interaction between friction and backlash in a feed drive system. The model consists of two equivalent masses, dual LuGre friction models, and a spring element to represent the elastic characteristics between the two masses. The ball screw drive system comprising a motor, screw, and table is divided into two subsystems: the motor-screw and the screw-table. Each subsystem is modeled using an equivalent mass and a LuGre friction model, while the elastic coupling between the two masses is represented by a linear spring. The LuGre model is employed to simulate the nonlinear behavior at the contact surfaces, and backlash is represented as the elastic deformation of the spring within the feed drive system. The contact mechanism between the two masses is divided into five stages, enabling a deeper understanding of the dynamic characteristics during velocity reversal. Model parameters are identified experimentally. A servo control loop is incorporated to evaluate tracking errors caused by friction and backlash. Comparisons between simulation and experimental results show that the proposed model achieves a maximum error of approximately 3.7%. Furthermore, the model offers physical insight into the tracking errors induced by friction and backlash.

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Cite This Study

Jian et al. (2025) studied this question.

synapsesocial.com/papers/6940223b2d562116f28fb8a7https://doi.org/10.1115/1.4070607
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