Energy-optimal trajectory problems in relative motion solved via Theory of Functional Connections
AffiliationSystems & Industrial Engineering, University of Arizona
Aerospace & Mechanical Engineering, University of Arizona
Spacecraft relative motion
Theory of functional connections
MetadataShow full item record
CitationDrozd, K., Furfaro, R., Schiassi, E., Johnston, H., & Mortari, D. (2021). Energy-optimal trajectory problems in relative motion solved via Theory of Functional Connections. Acta Astronautica, 182, 361-382.
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AbstractIn this paper, we present a new approach for solving a broad class of energy-optimal trajectory problems in relative motion using the recently developed Theory of Functional Connections (TFC). A total of four problem cases are considered and solved, i.e. rendezvous and intercept with fixed and free final time. Each problem is constrained and formulated using an indirect approach which casts the optimal trajectory problem as a system of linear or nonlinear two-point boundary value problems for the fixed and free final time cases, respectively. Using TFC, we convert each two-point boundary value problem into an unconstrained problem by analytically embedding the boundary constraints into a “constrained expression.” The latter includes a free-function that is expanded using Chebyshev polynomials with unknown coefficients. Regardless of the values of the unknown coefficients, the boundary constraints are satisfied and simple optimization schemes can be employed to numerically solve the problem (e.g. linear and nonlinear least-square methods). To validate the proposed approach, the TFC solutions are compared with solutions obtained via an analytical based method as well as direct and indirect numerical methods. In general, the proposed technique produces solutions to machine level accuracy. Additionally, for the cases tested, it is reported that computational run-time within the MATLAB implementation is lower than 28 and 300 ms for the fixed and free final time problems respectively. Consequently, the proposed methodology is potentially suitable for on-board generation of optimal trajectories in real-time.
Note24 month embargo; first published online 4 February 2021
VersionFinal accepted manuscript