Control of UAV quadrotor using reinforcement learning and robust controller

  • Zizuo Zhang
  • , Haiyang Yang
  • , Yuanyuan Fei
  • , Changyin Sun
  • , Yao Yu

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The control of unmanned aerial vehicle quadrotor is challenging because of non-linearities, coupling and disturbance. Here, a novel control method which includes reinforcement learning (RL) component and robust component is proposed. In this method, the RL component only relies on collected data instead of modelling to handle coupling and disturbance from aerodynamics and model. To ensure safety during training and improve training speed, the robust component is used to reduce the disturbance.The stability of the system with our controller is proven by Lyapunov method. The results of the simulation exhibit advanced performance of our controller.

Original languageEnglish
Pages (from-to)1599-1610
Number of pages12
JournalIET Control Theory and Applications
Volume17
Issue number12
DOIs
StatePublished - Aug 2023
Externally publishedYes

Keywords

  • adaptive control
  • intelligent control

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