期刊
IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
卷 -, 期 -, 页码 650-655出版社
IEEE
DOI: 10.1109/iecon43393.2020.9254310
关键词
Augmented Kalman filter observer; Force estimation; Force measurement; Force sensor offsets
类别
资金
- National Research Foundation of Korea (NRF) - Korea government (MSIP) [NRF-2019R1A2C2011444]
Low frequency dynamic force offsets and measurement noises make utilization of force sensor signal a difficult task, especially, the direct feedback of force measurements in force control systems. To solve these force sensor problems, a novel Kalman filter-based force observer that automatically estimates and eliminates force sensor offsets and attenuates measurement noises is developed in this paper. A dynamic model of force sensing system is derived taking into consideration the dynamic interaction among the motor, the load, and the force sensor between them, as well as the measurement equations. The state-space representation of dynamic force offsets is formulated and augmented to the system dynamic equations from which a state-space Kalman filter is designed. The properties of the designed Kalman filter are further theoretically analyzed in the transfer function form. To verify its effectiveness, experiments are carried out where performance comparison is made to that of a conventional Kalman filter. The proposed observer is found to perform better than the conventional one. Moreover, the transfer function form exhibits a simple structure which makes it simple to implement.
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