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首页> 外文期刊>International journal of computational methods >Online Parameter Estimation of the Lankarani-Nikravesh Contact Force Model Using Two Different Methods
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Online Parameter Estimation of the Lankarani-Nikravesh Contact Force Model Using Two Different Methods

机译：两种不同方法对Lancanani-Nikravesh接触力模型的在线参数估计

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Current contact force models are expected to be used under different environments, where the dynamical parameter estimation becomes an important issue in accurately analyzing the overall behavior of mechanical system especially for complex contact situations. In recent years, a significant amount of research has been carried out in relation to the nonlinear inverse problems, which can be generally divided into two categories: one is the linear method and the other can be called the nonlinear one. In this paper, both methods are described and compared. The linear method is based on the Taylor series and Exponentially Weighted Recursive Least Squares (EWRLS) estimation method. Whereas, the core of the nonlinear one is the Unscented Kalman Filter (UKF). The Lankarani-Nikravesh (L-N) contact force model is employed to quantify the contact effect in this paper, since it is proven to be more consistent with the physics of contact. Some simulation examples are employed to evaluate the convergence sensitivity of these two methods to parameter initial conditions. And the comparisons under the same simulation condition between both methods indicate that the nonlinear one is more robust and can converge faster than the linear one.
机译：当前的接触力模型有望在不同的环境下使用，其中动力学参数估计成为准确分析机械系统整体行为（尤其是复杂接触情况）的重要问题。近年来，关于非线性逆问题已经进行了大量研究，通常可以将其分为两类：一类是线性方法，另一类可以称为非线性方法。在本文中，将描述和比较这两种方法。线性方法基于泰勒级数和指数加权递归最小二乘（EWRLS）估计方法。非线性的核心是无味卡尔曼滤波器（UKF）。本文证明了Lankarani-Nikravesh（L-N）接触力模型可以量化接触效果，因为它被证明与接触物理更加一致。一些仿真示例被用来评估这两种方法对参数初始条件的收敛敏感性。两种方法在相同仿真条件下的比较表明，非线性方法比线性方法更鲁棒，并且收敛速度更快。

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