Nonlinear Adaptive Observer for Side Slip Angle and Road Friction Estimation

Liang Shao, Chi Jin, Cornelia Lex, Arno Eichberger

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

The side slip angle of a vehicle as well as the tire-road friction coefcient are important inputs for vehicle dynamics control system and automated driving modules. However measurement of these parameters are difcult and costly in mass production vehicles and need to be reliably and accurately estimated. We address the observer design problem for simultaneously estimating side slip angle and tire-road friction utilizing information from vehicle Electric Power Steering System (EPS). A key observation is that the vehicle dynamics can be transformed into a lower-triangular form. For non-afne parametrized systems in such a form we propose a nonlinear adaptive observer and prove the uniform exponential stability of the estimation error by constructing a strict Lyapunov function. The design procedure is subsequently applied to the vehicle observer design problem. Simulations demonstrate the robustness of the proposed observer against modeling error and measurement noise.
Original languageEnglish
Title of host publication55th IEEE Conference on Decision and Control (CDC 2016)
PublisherIEEE Computer Society
Pages6258-6265
Number of pages8
ISBN (Electronic) 978-1-5090-1837-6
DOIs
Publication statusPublished - 2016
Event55th IEEE Conference on Decision and Control (CDC 2016) -
Duration: 12 Dec 201614 Dec 2016

Conference

Conference55th IEEE Conference on Decision and Control (CDC 2016)
Period12/12/1614/12/16

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Keywords

  • nonlinear adaptive observer
  • sideslip angle estimation
  • road friction estimation

Cite this

Shao, L., Jin, C., Lex, C., & Eichberger, A. (2016). Nonlinear Adaptive Observer for Side Slip Angle and Road Friction Estimation. In 55th IEEE Conference on Decision and Control (CDC 2016) (pp. 6258-6265). IEEE Computer Society. https://doi.org/10.1109/CDC.2016.7799232