• DocumentCode
    630640
  • Title

    Formation flying of small satellites using suboptimal MPSP guidance

  • Author

    Joshi, Gauri ; Padhi, Radhakant

  • Author_Institution
    Dept. of Aerosp. Eng., Indian Inst. of Sci., Bangalore, India
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    1584
  • Lastpage
    1589
  • Abstract
    Using the recently developed model predictive static programming (MPSP), a suboptimal guidance logic is presented in this paper for formation flying of small satellites. Due to the inherent nature of the problem formulation, MPSP does not require the system dynamics to be linearized. The proposed guidance scheme is valid both for high eccentricity chief satellite orbits as well as large separation distance between chief and deputy satellites. Moreover, since MPSP poses the desired conditions as a set of `hard constraints´, the final accuracy level achieved is very high. The proposed guidance scheme has been tested successfully for a variety of initial conditions and for a variety of formation commands as well. Comparison with standard Linear Quadratic Regulator (LQR) solution (which serves as a guess solution for MPSP) and another nonlinear controller, State Dependent Riccati Equation (SDRE) reveals that MPSP guidance achieves the objective with higher accuracy and with lesser amount of control usage as well.
  • Keywords
    Riccati equations; artificial satellites; celestial mechanics; dynamic programming; predictive control; SDRE; chief satellite-deputy satellite separation distance; formation commands; hard constraints; high-eccentricity chief satellite orbits; initial conditions; model predictive static programming; small satellite formation flying; state dependent Riccati equation; suboptimal MPSP guidance; suboptimal guidance logic; Accuracy; Cost function; History; Orbits; Satellites; Trajectory; Vectors; MPSP; Model Predictive Static Programming; Satellite Formation Flying;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6580061
  • Filename
    6580061