Rapid Optimal Multi-Burn Ascent Planning and Guidance

Lu, Ping; Griffin, Brian J.; Dukeman, Greg A.; Chavez, Frank R.

doi:10.2514/6.2007-6773

Cited by 6 publications

(13 citation statements)

References 9 publications

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“…Thus p m = constant by Eq. (27). Since the final mass m(t f ) is free, the transversality condition for p m (t f ) is 22 p m (t f ) = 0 (33)…”

Section: Proofmentioning

confidence: 99%

Autonomous Trajectory Planning for Rendezvous and Proximity Operations by Conic Optimization

Liu

2012

AIAA Guidance, Navigation, and Control Conference

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Autonomous rendezvous and proximity operations (RPO) of spacecraft require the capability of on-board planning and executing highly constrained trajectories without ground support. This paper presents a general and rigorous methodology and algorithmic procedure toward this goal with the target vehicle that can be in an arbitrary orbit. The RPO problem is formulated as a nonlinear optimal control problem, subject to various state and control inequality constraints and equality constraints on interior points and terminal conditions. By a lossless relaxation technique, a relaxed problem is formed the solution of which is proven to be equivalent to that of the original RPO problem.The relaxed problem is then solved by a novel successive solution process, in which the solutions of a sequence of constrained subproblems with linear, time-varying dynamics are sought. After discretization, each of these problems becomes a second-order cone programming problem. Their solutions, if exist, are guaranteed to be found by a primal-dual interior-point algorithm. The efficacy of the proposed methodology is strongly supported by numerical experiments.

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“…Thus p m = constant by Eq. (27). Since the final mass m(t f ) is free, the transversality condition for p m (t f ) is 22 p m (t f ) = 0 (33)…”

Section: Proofmentioning

confidence: 99%

Autonomous Trajectory Planning for Rendezvous and Proximity Operations by Conic Optimization

Liu

2012

AIAA Guidance, Navigation, and Control Conference

Self Cite

View full text Add to dashboard Cite

show abstract

“…(3.17) involves a switching function S that determines when the vehicle is using full thrust or coasting [14,13,30].…”

Section: Hamiltonian and Additional Necessary Conditionsmentioning

confidence: 99%

“…The vacuum ascent optimization problem presented above has a semi-analytic solution [30,15]. The use of the linear gravity approximation in Eq.…”

Section: Analytical Ascent Solutionsmentioning

confidence: 99%

“…Regarding rapid mission planning, and especially the ability for in flight mission changes, the robustness of the algorithm is of the highest importance. To this end, algorithm convergence is enhanced using a multiple-shooting formulation [24] adding two additional nodes to the numerical problem [13,15,30]. One node is placed at the end of first burn,…”

Section: Multiple Shooting Formulationmentioning

confidence: 99%

“…For typical terminal constraints such as those in chapter (8), it can be seen that in the absence of thrust the condition H N T (τ f ) = 0 is automatically satisfied [30]. This allows the interior point necessary conditions to be expressed in a simplified form as…”

Section: Developmentmentioning

confidence: 99%

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Improvements to an analytical multiple-shooting approach for optimal burn-coast-burn ascent guidance

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Autonomous trajectory planning for space vehicles with a Newton–Kantorovich/convex programming approach

Xiao-ming

Zhang

2017

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Rapid Optimal Multi-Burn Ascent Planning and Guidance

Cited by 6 publications

References 9 publications

Autonomous Trajectory Planning for Rendezvous and Proximity Operations by Conic Optimization

Autonomous Trajectory Planning for Rendezvous and Proximity Operations by Conic Optimization

Improvements to an analytical multiple-shooting approach for optimal burn-coast-burn ascent guidance

Autonomous trajectory planning for space vehicles with a Newton–Kantorovich/convex programming approach

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