TR2012-099

Model Predictive Control Approach for Guidance of Spacecraft Rendezvous and Proximity Maneuvering


    •  Di Cairano, S.; Park, H.; Kolmanovsky, I., "Model Predictive Control Approach for Guidance of Spacecraft Rendezvous and Proximity Maneuvering", International Journal of Robust and Nonlinear Control, Vol. 22, No. 12, pp. 1398-1427, August 2012.
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      • @article{DiCairano2012jul,
      • author = {{Di Cairano}, S. and Park, H. and Kolmanovsky, I.},
      • title = {Model Predictive Control Approach for Guidance of Spacecraft Rendezvous and Proximity Maneuvering},
      • journal = {International Journal of Robust and Nonlinear Control},
      • year = 2012,
      • volume = 22,
      • number = 12,
      • pages = {1398--1427},
      • month = jul,
      • url = {http://www.merl.com/publications/TR2012-099}
      • }
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  • Research Areas:

    Advanced Control Systems, Mechatronics


Traditionally rendezvous and proximity maneuvers have been performed using open-loop maneuver planning techniques and ad hoc error corrections. In this paper, a Model Predictive Control (MPC) approach is applied to spacecraft rendezvous and proximity maneuvering problems in the orbital plane. We demonstrate that various constraints arising in these maneuvers can be effectively handled with the MPC approach. These include constraints on thrust magnitude, constraints on spacecraft positioning within Line-of-Sight (LOS) cone while approaching the docking port on a target platform, and constraints on approach velocity to match the velocity of the docking port. The two cases of a non-rotating and a rotating (tumbling) platform are treated separately, and trajectories are evaluated in terms of maneuver time and fuel consumption. For the case when the platform is not rotating and the docking port position is fixed with respect to the chosen frame, an explicit off-line solution of the MPC optimization problem is shown to be possible; this explicit solution has a form of a piecewise affine control law suitable for on-line implementation without an onboard optimizer. In the case of a fast rotating platform, it is, however, shown that the prediction of the platform rotation is necessary to successfully accomplish the maneuvers and to reduce fuel consumption. Finally, the proposed approach is applied to debris avoidance maneuvers with the debris in the spacecraft rendezvous path. The significance of this paper is in demonstrating that Model Predictive Control can be an effective feedback control approach to satisfy various maneuver requirements, reduce fuel consumption, and provide robustness to disturbances.