Novel Force Observer for Precise Force Estimation Using Force Sensor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - IECON 2020
Subtitle of host publication46th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Pages650-655
Number of pages6
ISBN (Electronic)9781728154145
DOIs
StatePublished - 18 Oct 2020
Event46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 - Virtual, Singapore, Singapore
Duration: 19 Oct 202021 Oct 2020

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2020-October

Conference

Conference46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
Country/TerritorySingapore
CityVirtual, Singapore
Period19/10/2021/10/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Augmented Kalman filter observer
  • Force estimation
  • Force measurement
  • Force sensor offsets

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