Full vehicle vibration state estimation algorithm based on feedback linearization

Yu Zhuang Zhao, Fan Lu, Si Zhong Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Aiming at the high-dimensional nonlinearity of full vehicle vibration system in the design of vehicle vibration state observer, a feedback linearization Kalman filter algorithm was proposed. Based on differential geometry theory, a nonlinear vehicle vibration model was transformed into a certain observable normal form via change of state coordinates. Based on the obtained linear system, the observer was designed by using Kalman filter algorithm. Finally the estimated states of nonlinear system were obtained through inverse transformation. Simulation results show that compared with extended Kalman observer, the proposed algorithm can improve the observation accuracy and operation efficiency of vehicle vibration states.

Original languageEnglish
Pages (from-to)1140-1145 and 1151
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume35
Issue number11
DOIs
Publication statusPublished - 1 Nov 2015

Keywords

  • Feedback linearization
  • Full vehicle
  • Nonlinear suspension
  • State estimation
  • Vibration

Fingerprint

Dive into the research topics of 'Full vehicle vibration state estimation algorithm based on feedback linearization'. Together they form a unique fingerprint.

Cite this