A nonlinear programming approach to space shuttle trajectory optimization

Space shuttle trajectory design requires the optimization of highly-constrained, branched, atmospheric trajectories. This paper presents a general mathematical model for trajectory optimization incorporating multiple simulation sections, state variable discontinuities, subarc elimination, branching, and six types of equality and inequality constraints. A solution is sought using a nonlinear programming approach based on SUMT, the sequential unconstrained minimization technique. Results of the numerical solution of a highly constrained space shuttle reentry problem are presented.

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