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Using Nonlinear Kalman Filter to Estimate the State of Nonlinear Semi-Active Suspension System

International Journal of Knowledge Based Computer Systems

Volume 1 Issue 2

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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