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Vehicle Handling Dynamics State Estimation Based on Strong Tracking Filter SCOPUS

Shu-en Zhao, Yu-ling Li, Xian Qu

보안공학연구지원센터(IJCA) International Journal of Control and Automation Vol.8 No.9 2015.09 pp.21-32

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

Due to some key state parameters of vehicle handling stability control are difficult to measure directly, the state optimization estimation algorithm of multi-sensor linear combination based on Strong Tracking Filter (STF) was proposed. Four degrees of freedom vehicle nonlinear dynamics model including longitudinal, lateral and roll motion were established. With the estimator of multi-sensors information fusion and the STF theory, the vehicle handling dynamics states estimation were simulated and analyzed. The result shows that the STF offers higher performance potential. Not only does it solve the problems of the state estimation value deviating from the true system states due to the model uncertainty, but also can inhibit the filtering divergence effectively. The technology of state estimation with the STF has wide range of adaptive tracking capability. It provides a real-time, accurate and low cost soft-sensing technology for vehicle advance control.

2

Strong Tracking Unscented Kalman Filtering Algorithm Based-on Satellite Attitude Determination System

Min Li, Bao-long Zhu, Song-yan Wang, Ying-chun Zhang, Hua-yi Li

보안공학연구지원센터(IJFGCN) International Journal of Future Generation Communication and Networking Vol.7 No.3 2014.06 pp.155-166

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

 
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