A Dual-Observer Design for Nonlinear Suspension System Based on Feedback Linearization

Abstract

A novel approach to estimate suspension state information and payload condition was developed in this article. A nonlinear quarter car model with air spring and damper was built. After verification of system observability and solvability, a certain coordinate transform was built to transform the nonlinear system into a linear one. Then a Kalman filter observer was applied. A sprung mass observer, which works cooperatively with suspension state information observer, was also designed. Designed dual-observer was verified under typical road profile and sprung mass disturbance. Compared with extended Kalman filter, the dual-observer showed better accuracy and robustness.