Position angular compensation for self-balance robot Based on Kalman filtering

Chao Quan Li, Xue Shan Gao*, Shu San Wang, Ke Jie Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper studies the compensation method based on low pass KF filter to eliminate the signal distortion caused by vibration or shock in angular position measurement system using single-axis accelerometers, and to improve the system stability. Least square fitting principle was used to build the posture angle calculation model, a hybrid low-pass filter was designed after getting the free frequency, and the physical test was implemented. The results show that the proposed compensation method can completely eliminate the signal distortion caused by high frequency vibrations, and it can also significantly improve the stability of self-balancing robot as well as the signal fluctuations caused by heavy impact.

Original languageEnglish
Pages (from-to)28-32
Number of pages5
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume32
Issue number1
Publication statusPublished - Jan 2012

Keywords

  • Compensation
  • Kalman blend filtering
  • Position angular signal
  • Self-balance robot

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