Vibration state estimation of nonlinear suspension system based on feedback linearization

Aiming at the nonlinearity of suspension system, a feedback linearization Kalman filter algorithm was proposed. Based on the differential geometry theory, the nonlinear vehicle vibration model was transformed into a certain observable normal form via the change of state coordinates. Based on the obtained linearized system, an observer was designed by using Kalman filter algorithm. Finally the estimated states of the nonlinear system were obtained through inverse transformation. The simulation results show that compared with the extended Kalman observer, the proposed algorithm can improve the observation accuracy of vehicle vibration states and reduce computational complexity.