A Smoothed GMS Friction Model Suited for Gradient-Based Friction State and Parameter Estimation

作者：Boegli Max^*; De Laet Tinne; De Schutter Joris; Swevers Jan

来源：IEEE/ASME Transactions on Mechatronics, 2014, 19(5): 1593-1602.

DOI：10.1109/TMECH.2013.2288944

• Friction
• Kalman filter
• state and parameter estimation

This paper presents a model that closely approximates the generalized Maxwell-Slip (GMS) model, a multistate 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 new model, referred to as the smoothed GMS (S-GMS) model, consists of an analytic set of differential equations. Such a model is well suited for gradient-based state and parameter estimation, as in the extended Kalman filter (EKF) or in moving horizon estimation. Similar to the GMS model, the S-GMS model is a multistate model that also describes all essential friction characteristics. Moreover, the S-GMS model description includes the single-state LuGre model and Elastoplastic model as special cases. This paper also discusses the implementation of the EKF estimator for the S-GMS friction model and compares its performance to the LuGre model in joint state and parameter estimation.

• 出版日期2014-10