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Robust Formation Control for Cooperative Underactuated Quadrotors via Reinforcement Learning

  • Wanbing Zhao
  • , Hao Liu*
  • , Frank L. Lewis
  • *Corresponding author for this work
  • Beihang University
  • University of Texas at Arlington

Research output: Contribution to journal › Article › peer-review

Abstract

In this article, the model-free robust formation control problem is addressed for cooperative underactuated quadrotors involving unknown nonlinear dynamics and disturbances. Based on the hierarchical control scheme and the reinforcement learning theory, a robust controller is proposed without knowledge of each quadrotor dynamics, consisting of a distributed observer to estimate the position state of the leader, a position controller to achieve the desired formation, and an attitude controller to control the rotational motion. Simulation results on the multiquadrotor system confirm the effectiveness of the proposed model-free robust formation control method.

Original languageEnglish
Pages (from-to)4577-4587
Number of pages11
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume32
Issue number10
DOIs
StatePublished - 1 Oct 2021

Keywords

  • Formation control
  • quadrotor system
  • reinforcement learning (RL)
  • robust control
  • underactuated system

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