A Trajectory Tracking Method Using Convex Optimization

Ze An, Fen Fen Xiong, Chao Li

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

1 Citation (Scopus)

Abstract

To improve the efficiency of the existing convex optimization-based trajectory tracking method, and address the issue that the existing trajectory tracking methods are very sensitive to the deviations of axial states, a new trajectory tracking method using convex optimization in conjunction with a modified receding horizon control strategy is developed in this paper. The trajectory tracking is implemented in each segment of trajectory in successive using the convex optimization method. To ensure online guidance, the optimal control problem of trajectory tracking in each segment is transformed into an exact convex optimization, which can be solved in only one iteration. Meanwhile, to address the deviation of axial states, a time re-planning method is proposed to ensure the accuracy and robustness of trajectory tracking. Simulation results show that the proposed methods can track the reference trajectory with high accuracy and robustness with respect to various disturbances.

Original languageEnglish
Title of host publicationProceedings of the 39th Chinese Control Conference, CCC 2020
EditorsJun Fu, Jian Sun
PublisherIEEE Computer Society
Pages3281-3287
Number of pages7
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

  • Axial states deviation
  • Convex optimization
  • Receding horizon control
  • Trajectory tracking

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