Optimal trajectory tracking control for automated guided vehicles

A. Das, Y. Kasemsinsup, S. Weiland

Research output: Contribution to journalConference articlepeer-review

7 Citations (Scopus)
12 Downloads (Pure)

Abstract

This work presents a control strategy for the trajectory tracking problem of an Automated Guided Vehicle (AGV). In contrast to the current methods, this design strategy remains invariant and flexible to arbitrary number of wheels. A three-stage cascade control strategy is proposed in which the control design for the vehicle chassis is separated from the wheel-tire modules. For a given vehicle reference trajectory, the outer controller determines the required forces and moment inputs to the vehicle chassis in a time-receding fashion. At the second stage, the required forces and moment inputs are optimally allocated for each wheel and tire. At each wheel-tire module, a nonlinear controller is used to determine the actual control input for the wheel actuators. The performance of the presented control strategy is illustrated through simulation results with a realistic driving scenario for a six-wheeled vehicle. We demonstrate that the proposed controller architecture is configurable for an arbitrary number of wheels and capable of handling large steering angles efficiently.

Original languageEnglish
Pages (from-to)303–308
Number of pages6
JournalIFAC-PapersOnLine
Volume50
Issue number1
DOIs
Publication statusPublished - 31 Jul 2017
Event20th World Congress of the International Federation of Automatic Control (IFAC 2017 World Congress) - Toulouse, France
Duration: 9 Jul 201714 Jul 2017
Conference number: 20
https://www.ifac2017.org/

Keywords

  • Trajectory tracking
  • path following
  • Decentralized control
  • Systems
  • Autonomous Vehicles
  • Motion control
  • Path Following
  • Decentralized Control
  • Trajectory Tracking
  • Decentralized Control and Systems
  • Trajectory Tracking and Path Following

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