Robust NMPC strategy for solar sail trajectory control in uncertain environments

This work presents a nonlinear model predictive control (NMPC) framework for robust trajectory optimization of solar sail-propelled spacecraft. Solar sail trajectory design is inherently challenging due to the coupling between the sail attitude dynamics and the spacecraft orbital motion, and the presence of significant uncertainties. Traditional open-loop optimal control methods are often inadequate for handling these uncertainties, including those related to orbital insertion, state observation, and solar sail propulsion. The proposed NMPC approach discretizes the dynamics of the system into a finite number of arcs, with control inputs held constant in each arc. By incorporating a nominal dynamical model, NMPC generates an optimal trajectory. This solution is then periodically updated to mitigate the effects of environmental uncertainties not accounted for in the nominal model. The effectiveness of the NMPC framework is demonstrated through simulations of various three-dimensional time-optimal interplanetary transfer scenarios. Results show that NMPC exhibits high robustness, enabling the spacecraft to successfully reach its target destination even in the presence of multiple simultaneous uncertainties.