An Improved Model Predictive Control Method for Vehicle Lateral Control

Yunao Li, Senchun Chai, Ruiqi Chai, Xiaopeng Liu

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

4 Citations (Scopus)

Abstract

This paper presents a lateral dynamic model based on control algorithm for the path tracking of autonomous vehicle. To improve the stability of the vehicle for high speed cases, an improved model predictive control (MPC) controller has been proposed in this paper. By combining the steady state response and MPC, the lateral motion of the autonomous vehicle can be controlled smoothly and the accuracy of path tracking can be guaranteed at a high speed. A number of simulation results obtained by using MATLAB are provided to validate this methodology.

Original languageEnglish
Title of host publicationProceedings of the 39th Chinese Control Conference, CCC 2020
EditorsJun Fu, Jian Sun
PublisherIEEE Computer Society
Pages5505-5510
Number of pages6
ISBN (Electronic)9789881563903
DOIs
Publication statusPublished - Jul 2020
Event39th Chinese Control Conference, CCC 2020 - Shenyang, China
Duration: 27 Jul 202029 Jul 2020

Publication series

NameChinese Control Conference, CCC
Volume2020-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference39th Chinese Control Conference, CCC 2020
Country/TerritoryChina
CityShenyang
Period27/07/2029/07/20

Keywords

  • Autonomous vehicle
  • Lateral dynamics
  • Model predictive control
  • Stability
  • Steady state response

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