Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

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


Affiliations
1 Shiraz University, Shiraz, Iran, Islamic Republic of
     

   Subscribe/Renew Journal


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
Subscription Login to verify subscription
User
Notifications
Font Size


Abstract Views: 382

PDF Views: 0




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

Abstract Views: 382  |  PDF Views: 0

Authors

A. Tadayoninejad
Shiraz University, Shiraz, Iran, Islamic Republic of
F. Shabaninia
Shiraz University, Shiraz, Iran, Islamic Republic of

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