Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. Vehicle Nonlinear State Estimation Procedure
  2.1. Vehicle Nonlinear State Estimation Principle
  2.2. Strong Tracking Filter Design
  2.3. Optimal Estimate of Multi-sensors Linear Combination
 3. Vehicle Handling Dynamics State Estimation with STF
  3.1. Vehicle Nonlinear Dynamic Modeling
  3.2. Vehicle State Estimation Based on STF
 4. Simulation and Analysis
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Shu-en Zhao [ College of Mechantronics and Automobile Engineering, Chongqing JiaoTong University, Chongqing, China ]
• Yu-ling Li [ College of Mechantronics and Automobile Engineering, Chongqing JiaoTong University, Chongqing, China ]
• Xian Qu [ College of Mechantronics and Automobile Engineering, Chongqing JiaoTong University, Chongqing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605