Robust Parametric Shrinking Horizon Model Predictive Control and its Application to Spacecraft Rendezvous

This letter introduces a robust Model Predictive Control approach in which a shrinking prediction horizon and a system input parameterization are exploited to control a linear system with set-bounded disturbances while satisfying state and control constraints. By exploiting input parameterization, the number of decision variables in the optimal control problem and the computational time can be reduced. The simulated spacecraft rendezvous maneuver is used to highlight the potential of the proposed approach for practical applications.