移动地平线摩擦状态的光滑GMS摩擦模型及参数估计

M. Boegli, T. Laet, J. Schutter, J. Swevers
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引用次数: 23

摘要

本文提出了一种近似于广义麦克斯韦-滑移(GMS)模型的光滑摩擦模型,该模型是一种多状态摩擦模型,可以描述预滑和滑动运动中的所有基本摩擦特性。光滑GMS (S-GMS)模型由一组微分方程组成,非常适合在线状态和参数估计,例如在移动视界估计(MHE)中。与GMS模型相反,GMS模型由一个开关结构来适应其混合性质。有效的在线状态和参数估计是基于模型的摩擦补偿的关键,以跟踪摩擦特性在时间和空间上的变化。此外,已知MHE比扩展卡尔曼滤波(EKF)能更好地处理模型非线性、干扰和约束。本文讨论了GMS和S-GMS摩擦模型的EKF和MHE估计器的实现。结果表明,MHE与S-GMS模型相结合的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Smoothed GMS friction model for Moving Horizon friction state and parameter estimation
This paper presents a smoothed friction model that closely approximates the Generalized Maxwell-Slip (GMS) model, a multi-state friction model known to describe all essential friction characteristics in presliding and sliding motion. In contrast to the GMS model, which consists of a switching structure to accommodate for its hybrid nature, the Smoothed GMS (S-GMS) model consists of an analytic set of differential equations well suited for on-line state and parameter estimation, such as in Moving Horizon Estimation (MHE). Efficient on-line state and parameter estimation is essential for model-based friction compensation in order to track friction characteristics changes in time and space. Moreover, MHE is known to better handle model nonlinearities, disturbances and constraints than Extended Kalman Filter (EKF). This paper discusses the implementation of the EKF and MHE estimators for both the GMS and the S-GMS friction models. The benefit of the combination of MHE and S-GMS model is shown.
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