Feedback Linearization Kalman Observer Based Sliding Mode Control for Semi-Active Suspension Systems

Zheng Liu, Hongbin Ren*, Sizhong Chen, Yong Chen, Jianbo Feng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

In this paper, a new approach for an observer based controller for semi-active suspension systems is presented. The observer part is a feedback linearization Kalman filter which is based on differential geometry. The original nonlinear system is transferred to a linear system by certain coordinate transfer after the verification of observability and solvability of the system observer design problem under certain sensor placement configurations. Then, a linear Kalman filter algorithm can be applied to the linearized system. The state information can be obtained through an inverse coordinate transfer of the estimation results of the linear Kalman filter. The observer is verified by a simulation test under different road profiles, and a comparison between the designed observer and extended Kalman filter shows that the feedback linearization Kalman filter has better performance. A model reference sliding mode controller based on the estimation results of the observer is also proposed. A rig test system for the semi-active suspension system is implemented, and, both the designed observer and controller are verified through the rig test. Experimental results show that the proposed new approach for semi-active suspension control can significantly improve vehicle ride comfort with common and low-cost sensors.

Original languageEnglish
Article number9066842
Pages (from-to)71721-71738
Number of pages18
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

Keywords

  • Kalman filter
  • Semi-active suspension
  • feedback linearization
  • observer design

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