International Journal of Distributed and Cloud Computing

2013 | Volume 1 | Issue 2

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

1. A. Tadayoninejad – Shiraz University, Shiraz, Iran

2. F. Shabaninia – Shiraz University, Shiraz, Iran

Received
14-Mar-2014 		Accepted
- 		Published
14-Mar-2014
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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