Drones (Nov 2022)

Prescribed Performance Rotating Formation Control of Multi-Spacecraft Systems with Uncertainties

  • Yan Liu,
  • Kaiyu Qin,
  • Weihao Li,
  • Mengji Shi,
  • Boxian Lin,
  • Lu Cao

DOI
https://doi.org/10.3390/drones6110348
Journal volume & issue
Vol. 6, no. 11
p. 348

Abstract

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This paper investigates the problem of rotating formation control for multi-spacecraft systems with prescribed performance in the presence of model uncertainties. Firstly, The spacecraft dynamics containing unmodelled parts is described in a polar coordinate system, which is to solve the problem of the controllable angular velocity of rotating formation. Then, the prescribed performance control method is improved by developing new prescribed performance functions. Based on the improved prescribed performance control method, the distributed controller is designed for multi-spacecraft systems to achieve rotating formations with prescribed performance, i.e., the formations error converges to a predefined arbitrarily small residual set, with convergence time no less than a prespecified value. And an RBF neural network is used to fit the unmodelled components of the spacecraft dynamics. Compared with the existing works of literature, this paper not only solves the robust prescribed performance rotating formation control of multi-spacecraft system, but also acheives rotating formation with adjustable angular velocity. Finally, the Lyapunov approach is employed for convergence analysis, and simulation results are provided to illustrate the effectiveness of the theoretical results.

Keywords