Low-thrust trajectory design using closed-loop feedback-driven control laws and state-dependent parameters

Harry Holt, Roberto Armellin, Andrea Scorsoglio, Roberto Furfaro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations


Low-thrust many-revolution trajectory design and orbit transfers are becoming increasingly important with the development of high specific impulse, low-thrust engines. Closed-loop feedback-driven (CLFD) control laws can be used to solve these trajectory design problems with minimal computational cost and offer potential for autonomous guidance. However, they have user-defined parameters which limit their optimality. In this work, an actor-critic reinforcement learning framework is proposed to make the parameters of the Lyapunov-based Q-law state-dependent, ensuring the controller can adapt as the dynamics evolve during a transfer. The proposed framework should be independent of the particular CLFD control law and provides improved solutions for mission analysis. There is also potential for future on-board autonomous use, as trajectories are closed-form and can be generated without an initial guess. The current results focus on GTO-GEO transfers in Keplerian dynamics and later with eclipse and J2 effects. Both time-optimal and mass-optimal transfers are presented, and the stability to uncertainties in orbit determination are discussed. The task of handling orbit perturbations is left to future work.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2020 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105951
StatePublished - 2020
EventAIAA Scitech Forum, 2020 - Orlando, United States
Duration: Jan 6 2020Jan 10 2020

Publication series

NameAIAA Scitech 2020 Forum
Volume1 PartF


ConferenceAIAA Scitech Forum, 2020
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Aerospace Engineering


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