Axel Garcia, Massachusetts Institute of Technology; Richard Linares, Massachusetts Institute of Technology; Zachary Folcik, MIT Lincoln Laboratory; Peter Niedfeldt, MIT Lincoln Laboratory; James Gandek, MIT Lincoln Laboratory; Christopher M Jewison, The Charles Stark Draper Laboratory, Inc; Paul Cefola, University at Buffalo (SUNY)
Keywords: direct optimization, proximity operations, NMCs, low-thrust, electric propulsion, optimal control
Abstract:
The main goal of this research is to build a toolset to enable mission trajectory planning using low-thrust platforms. More specifically, the Electric Propulsion Intelligent Control (EPIC) project aims to analyze operations including low-thrust transfers, chaser satellite orbiting around a Natural Motion Circumnavigation (NMC) target’s orbit, and flybys aimed at proximity operations in LEO. In this paper, we derive analytical approximations for high-thrust/low-thrust proximity operations. In addition, direct and indirect control methods are implemented for multi-segment optimization with two MATLAB compatible optimization programs: Hp-adaptive Gaussian Quadrature Collocation and Sparse Nonlinear Programming Software (GPOPS-II) and a Nonlinear Optimization Software (NLOPT). We compute optimal low-thrust trajectories with both methods with the goal of comparing and performing proximity operations between satellites. The propagator in both programs is capable to run up to a 4×4 geopotential model, atmospheric drag and both spacecraft consist of 500kg of payload mass, 40-Watt electric thruster which operates at a variable specific impulse (i.e., Isp). Additionally, we provide controller-agnostic safety analysis based on control barrier functions to certify collision avoidance during proximity operations, even under unknown but bounded perturbations or adversarial disturbances. This research has numerous guidance and control applications for achieving mission success and safety in autonomous operations.
Date of Conference: September 14-17, 2021
Track: Conjunction/RPO