Estimation accuracy and robustness analysis of a state observer for an active vehicle suspension

In designing a state observer for the suspension applications, the suitable selection of measurement signals is one of the important issues to achieve good estimation accuracy and meanwhile to ensure the system stability and also with the minimum sensor requirements. This paper investigates the estimation accuracy along with the robustness performance of a Kalman filter active vehicle suspension system and five different combinations of the measured states were compared. Simulations show the results of practical significance which will be useful for Kalman filter design in active vehicle suspension system.