Publications
Minduli Wijayatunga, Prof Roberto Armellin, Dr Harry Holt, Dr Laura Pirovano and Prof Claudio Bombardelli
A convex-optimization-based model predictive control (MPC) algorithm for the guidance of active debris removal missions is proposed in this work. A high-accuracy reference for the convex optimization is obtained through a split- Edelbaum approach that takes the effects of J2, drag, and eclipses into account. When the spacecraft deviates significantly from the reference trajectory, a new reference is calculated through the same method to reach the target debris. When required, phasing is integrated into the transfer. During the mission, the phase of the spacecraft is adjusted to match that of the target debris at the end of the transfer by introducing intermediate waiting times. The robustness of the guidance scheme is tested in a high-fidelity dynamic model that includes thrust errors and misthrust events. The guidance algorithm performs well without requiring successive convex iterations. Monte Carlo simulations are conducted to analyze the impact of these thrust uncertainties on the guidance. Simulation results show that the proposed convex-MPC approach can ensure that the spacecraft can reach its target despite significant uncertainties and long-duration misthrust events.
Minduli Wijayatunga, Prof Roberto Armellin and Dr Laura Pirovano
This Engineering Note has proposed practical techniques to improve the convergence of indirect trajectory optimization methods when solving Fuel and Time optimal problems. By introducing a scaling constant in the Fuel optimal objective function, a good transition from the Energy optimal to the Fuel optimal problem is achieved. This approach used a low number of iterations to reach convergence compared to other methods in the literature. Similarly, it was shown that Energy optimal can provide a good guess for the presented Time optimal problems and that introducing another scaling constant to the objective function can reduce the initial residuals and improve convergence. For the selected test cases, this approach brings advantages in both the computational efficiency and convergence rate when compared with the traditional continuation methods.
Minduli Wijayatunga, Prof Roberto Armellin, Dr Harry Holt, Dr Laura Pirovano and Dr Aleksander Lidtke
Space debris have become exceedingly dangerous over the years as the number of objects in orbit continues to increase. Active debris removal (ADR) missions have gained significant interest as effective means of mitigating the risk of collision between objects in space. This study focuses on developing a multi-ADR mission that utilizes controlled reentry and deorbiting. The mission comprises two spacecraft: a Servicer that brings debris to a low altitude and a Shepherd that rendezvous with the debris to later perform a controlled reentry. A preliminary mission design tool (PMDT) was developed to obtain time and fuel optimal trajectories for the proposed mission while considering the effect of J2, drag, eclipses, and duty cycle. The PMDT can perform such trajectory optimizations for multi- debris missions with computational time under a minute. Three guidance schemes are also studied, taking the PMDT solution as a reference to validate the design methodology and provide guidance solutions to this complex mission profile.
