Skip to main navigation Skip to search Skip to main content

Optimal robust path tracking control for multi-constrained underactuated vehicles based on uncertainty orthogonal decomposition

  • Xinrong Zhang
  • , Quanning Xu
  • , Xinle Gong*
  • , Jin Huang*
  • , Xiaomin Zhao
  • , Xueyun Li
  • *Corresponding author for this work
  • Chang'an University
  • Tsinghua University
  • Hefei University of Technology
  • Wuhan University of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In this article, an optimal robust constraint-following control is proposed for the underactuated vehicle path tracking problem. First, an underactuated dynamic model is established according to Udwadia–Kalaba (UK) equation, and the system uncertainty is decomposed into matching and mismatching portions based on the system geometric characteristics. The mismatching uncertainty is orthogonal to task space; thus, its influence on system stability is eliminated. Second, the diffeomorphism method is used to creatively set inequality and equality constraints into new equality constraints, and a robust control method for front steering vehicles with parameter-tunable is proposed. Third, an optimal design scheme is proposed for the tunable parameters to minimize the comprehensive index of system performance and control cost. Carsim-Simulink co-simulation shows the effectiveness of the proposed optimal robust control. This article creatively solves the problem of optimal robust control for path tracking of multi-constrained underactuated vehicles.

Original languageEnglish
Pages (from-to)890-905
Number of pages16
JournalJVC/Journal of Vibration and Control
Volume30
Issue number3-4
DOIs
Publication statusPublished - Feb 2024
Externally publishedYes

Keywords

  • autonomous vehicles
  • optimal design
  • path tracking
  • robust control
  • underactuated systems

Fingerprint

Dive into the research topics of 'Optimal robust path tracking control for multi-constrained underactuated vehicles based on uncertainty orthogonal decomposition'. Together they form a unique fingerprint.

Cite this