TR2021-005

Model Predictive Control Approach for Autonomous Sun-Synchronous Sub-Recurrent Orbit Control


    •  Hayashi, N., Weiss, A., Di Cairano, S., "Model Predictive Control Approach for Autonomous Sun-Synchronous Sub-Recurrent Orbit Control", AIAA SciTech, DOI: https:/​/​doi.org/​10.2514/​6.2021-1953, January 2021.
      BibTeX TR2021-005 PDF
      • @inproceedings{Hayashi2021jan,
      • author = {Hayashi, Naohiro and Weiss, Avishai and Di Cairano, Stefano},
      • title = {Model Predictive Control Approach for Autonomous Sun-Synchronous Sub-Recurrent Orbit Control},
      • booktitle = {AIAA SciTech},
      • year = 2021,
      • month = jan,
      • publisher = {AIAA},
      • doi = {https://doi.org/10.2514/6.2021-1953},
      • url = {https://www.merl.com/publications/TR2021-005}
      • }
  • MERL Contacts:
  • Research Areas:

    Control, Dynamical Systems

Abstract:

In recent years, control of satellites without resorting to ground stations, i.e., autonomous satellite control, has attracted significant interest due to the potential of providing high precision, flexibility, and reduced operating costs. In this paper we consider the autonomous satellite control in a Sun-synchronous Sub-recurrent orbit (SSO), in Very Low Earth Orbit (VLEO). We propose a linear time-varying Model Predictive Control (MPC) for SSO formulated based on Relative Orbital Elements (ROE). The MPC capabilities of handling multi-input multi-output systems subject to constraints, its predictive nature, and the usage of ROE in the cost function enables to control SSO keeping and transferring based on the ground trace, while also accounting for coasting phases where propulsion should not be engaged. The proposed method also has limited computational burden, since linear MPC requires solving a convex quadratic program for which efficient and compact solvers exists. We assess the performance of the proposed method by simulations in closed-loop with both, a nonlinear model of the satellite orbital dynamics and the GMAT simulation toolkit.