Estimation of Road Profile for Suspension Systems Using Adaptive Super-Twisting Observer

被引：0
作者：
Rath, J. J. [1 ]
Veluvolu, Kalyana C. [1 ]
Defoort, Michael [2 ]
机构：
[1] Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daegu 702701, South Korea
[2] Univ Lille Nord France, UVHC, CNRS UMR 8201, LAMIH, F-59313 Valenciennes, France
来源：
2014 EUROPEAN CONTROL CONFERENCE (ECC) | 2014年
关键词：
SLIDING MODE OBSERVERS; ORDER;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The performance evaluation of active suspension system of vehicle is critically reliant on estimation of random road roughness profile. In this paper, the nonlinear dynamics of spring and damper of the active suspension system are considered to develop a nonlinear model excited by the random road excitation profile as an unknown input. To estimate the unknown input, an adaptive super-twisting algorithm based observer is designed for estimation of the road profile and states of the system. Under Lipschitz conditions, the convergence of the error dynamics is then proven. The effectiveness of the proposed observer for state and unknown input estimation is shown through simulation results performed for the Ford Fiesta MK2 vehicle suspension dynamics.
引用
收藏
页码：1675 / 1680
页数：6
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