Overview
Low thrust spacecraft, which may be required to thrust for months to years at a time, are susceptible to missed thrust events (MTE). The occurrence of these MTEs are inherently random and can be caused by anything from a software glitch to a micrometeoroid strike. This work is focused on designing trajectories resilient to MTEs and opens up exciting possibilities for the design of MTE resilient trajectories.
Papers (Reverse Chronological Order)
Design of Solar Sailing Trajectories Resilient to Safe Mode Events – Astrodynamics Specialist Conference 2020 – With Carrie Grace Sandel, James Pezent, Rohan Sood, Frank Laipert, Andrew Heaton, & Les Johnson – We expand our work on designing missed thrust evnet resilient trajectories to solar sailcraft.
Designing trajectories resilient to missed thrust events using expected thrust fraction – Aerospace Science and Technology – With Carrie Grace Sandel, Rohan Sood & Frank Laipert – We expand our work on embed missed thrust events into the trajectory design process. A large increase in resilience to missed thrust events is shown over several interplanetary example trajectories.
Expected Thrust Fraction: Resilient Trajectory Design Applied to the Earth Return Orbiter – Space Flight Mechanics Meeting 2020 – With Rohan Sood & Frank Laipert – We further explore Expected Thrust Fraction by applying it to the Earth Return Orvbiters outbound Earth to Mars trajectory at the mid-fidelity level.
Designing Trajectories Resilient to Missed Thrust Events Using Expected Thrust Fraction – Astrodynamics Specialist Conference 2020 – With Carrie Grace Sandel, Rohan Sood & Frank Laipert – We explore how to embed MTE’s as a time-dependent duty cycle. Determining this duty cycle is a separable sub-problem, and a well-behaved approximation for it is developed. Finally, increased resiliency to MTEs is shown through numerical simulation.
Using Reinforcement Learning to Design Missed Thrust Resilient Trajectories – Astrodynamics Specialist Conference 2020 – With Kyra Bryan, Rohan Sood & Frank Laipert – We explore how reinforcement learning can be used to improve a neural network’s recovery from missed thrust events.