Robust adaptive recursive sliding mode attitude control for a quadrotor with unknown disturbances

Lulu Chen, Zhenbao Liu, Honggang Gao, Guodong Wang

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

Model uncertainties, unknown disturbances, and sensors measurement noises affect the attitude tracking control performance of quadrotors. In this article, a novel robust adaptive recursive sliding mode control (ARSMC) strategy is proposed for the quadrotor to improve the attitude tracking performance and disturbance rejection. Firstly, recursive sliding mode control is introduced, including a two-layer sliding surface, an integral sliding surface, and a fast nonsingular terminal sliding surface, which are recursive. Both sliding surfaces converge to zero in turn. And the initial value of the integral sliding surface is designed to eliminate the reaching phase. Besides, the adaptive gain adjustment method is presented to make an estimate of the unknown upper bound of disturbances. It is proved that the attitude control system has the finite-time convergence and the attitude tracking error will converge to zero. A quadrotor attitude test platform is built to evaluate the proposed algorithm. For comparison, twisting controller (TC), cascade PID, and active disturbance rejection control (ADRC) algorithms are introduced. Ultimately, the efficiency and feasibility of the proposed algorithm are verified by simulation and experimental results.

Original languageEnglish
Pages (from-to)114-125
Number of pages12
JournalISA Transactions
Volume122
DOIs
StatePublished - Mar 2022

Keywords

  • Adaptive recursive sliding mode control (ARSMC)
  • Attitude control
  • Finite-time control
  • Quadrotor
  • Robust control

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