Using Nonlinear Kalman Filter to Estimate the State of Nonlinear Semi-Active Suspension System
Published: 2013
Author(s) Name: A. Tadayoninejad, F. Shabaninia |
Author(s) Affiliation: Shiraz University, Shiraz, Iran
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Abstract
A nonlinear method is used to estimate the state of the
nonlinear semi-active suspension system. To estimate
the state of the nonlinear semi-active suspension
system, a nonlinear method is required. In this study,
two nonlinear estimators including the Extended Kalman
Filter (EKF) and the Unscented Kalman Filter (UKF) are
used. EKF uses first order Taylor expansion while the
UKF performs stochastic linearization to approximate
the nonlinear system. A comparison between true
value and state estimation of nonlinear semi-active
suspension system based on EKF and UKF have
been done and by the aid of these estimations, Sky –
Hook controller and output feedback PD controller are
designed. Simulations show the effectiveness of using
two nonlinear Kalman filters in estimating the state of a
nonlinear suspension system.
Keywords: Sky-Hook, Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), State Estimation, Suspension Model, Output feedback PD Controller
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