Minimum-Fuel Powered Descent for Mars Pinpoint Landing

Topcu, Ufuk; Casoliva, Jordi; Mease, Kenneth D.

doi:10.2514/1.25023

Cited by 62 publications

(26 citation statements)

References 17 publications

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“…Among the few studies on primer vector theory applied to vehicle formations, it is worth noting the work of Mailhe & Guzman (2004), where the formation initialization problem is addressed. Applications of primer vector theory to 6 DoF single vehicles have been employed to optimize the descent on Mars (Topcu et al, 2007). These studies, however, assume that the spacecraft is subject to a constant gravity acceleration, the control variables are the translational acceleration and the angular rates, and the translational acceleration can be pointed in any direction by rotating the vehicle.…”

Section: Analytical and Numerical Approaches To The Optimal Path Planmentioning

confidence: 99%

A Variational Approach to the Fuel Optimal Control Problem for UAV Formations

Haddad¹

2012

Recent Advances in Aircraft Technology

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Section: Analytical and Numerical Approaches To The Optimal Path Planmentioning

confidence: 99%

A Variational Approach to the Fuel Optimal Control Problem for UAV Formations

Haddad¹

2012

Recent Advances in Aircraft Technology

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“…Topcu et al have indeed shown that the general case of the propellant-optimal solution follows a max-min-max bang-bang structure (up to first-order conditions). 21,22 They also show that degenerate cases of this general profile can occur that are still propellant optimal, namely max and min-max. For the general max-min-max case, the individual thrust arcs typically serve the purpose of corrective maneuvers, e.g., targeting the landing site (max), coast to the landing site and pitching up (min), and finally nulling of the remaining velocity (max).…”

Section: E Observations On the Optimal Solution Of The Tpbvpmentioning

confidence: 93%

Guidance for Autonomous Precision Landing on Atmosphereless Bodies

Gerth

Mooij

2014

AIAA Guidance, Navigation, and Control Conference

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Two key technologies that will likely fly on next-generation planetary landers are hazard detection and avoidance (HDA) and vision-based navigation. The purpose of HDA is to make previously unsafe landing sites accessible by future vehicles, and to increase the safe landing probability overall. Vision-based navigation will enable to target specific landing sites more precisely and also plays an important role for HDA. This paper formulates requirements on the guidance system that derive from the needs of these new systems. After the introduction of a reference mission scenario with HDA and vision-based navigation inthe-loop, an extensive literature survey of the state-of-the-art in approach-phase guidancealgorithms is presented. This presents the methods under the angle of HDA-compatibility. The sheer number of papers mentioned here leads to the conclusion that trade-offs are challenging. It is recommended to do a down-selection from the papers presented here, and do a performance-based trade study for the particular test case under consideration with a few candidates. As an example, E-Guidance is presented for a Mercury-and a Moon-landing scenario. Because the results differ dramatically, it is concluded that it is essential to perform trade-offs on the actual mission scenario under study, and that trades cannot merely be based on references in the literature. Because the proposed E-Guidance method is not satisfyingly robust, it is a goal for future research to improve upon this.

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“…Given the constraints, the dynamics, and a target location on the surface (0, q) T where q ∈ R 2 are the surface landing coordinates, the planetary soft landing problem is formulated as the following prioritized optimization problem: Er(t f ) − q (6) subject to the following, ∀t ∈ [0, t f ]: the dynamics in (1), (11) subject to the following, ∀t ∈ [0, t f ]: the dynamics in (1),…”

Section: Planetary Soft Landing Problem With Pointing Constraintsmentioning

confidence: 99%

“…These approaches provide guidance solutions that have a limited envelop of initial states from which a spacecraft can maneuver toward the desired target without violating the physical state and control constraints [11]. Other methods enforce the appropriate constraints but with nonlinear optimization [6], [7], which has no guarantee on convergence time or that the most fuel optimal solution will be found.…”

Section: Introductionmentioning

confidence: 97%

Lossless convexification of Powered-Descent Guidance with non-convex thrust bound and pointing constraints

Carson

Açıkmeşe

Blackmore

2011

Proceedings of the 2011 American Control Conference

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A numerically-efficient, convex formulation of PDG (Powered-Descent Guidance) for Mars pinpoint and precision landing has been enhanced to include thrust pointing constraints. The original algorithm was designed to enforce both control and state constraints, including maximum and minimum thrust bounds, maximum speed limits and descent within a glideslope cone (surface impact avoidance). The thrust bounds are non-convex, so the original formulation developed a lossless convexification of these constraints. Likewise, thrust pointing constraints are non-convex. In this paper we present a relaxation for the thrust pointing constraint such that the enhanced PDG algorithm generates a lossless convexification for both the thrust bound and thrust pointing constraints. Pointing constraints are needed for onboard terrain-relative sensors that have specific field-of-view requirements during landing.

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Minimum-Fuel Powered Descent for Mars Pinpoint Landing

Cited by 62 publications

References 17 publications

A Variational Approach to the Fuel Optimal Control Problem for UAV Formations

A Variational Approach to the Fuel Optimal Control Problem for UAV Formations

Guidance for Autonomous Precision Landing on Atmosphereless Bodies

Lossless convexification of Powered-Descent Guidance with non-convex thrust bound and pointing constraints

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