GNC robustness stability verification for an autonomous lander

Pagone, Michele; Novara, Carlo; Martella, P.; Nocerino, Claudio

doi:10.1016/j.ast.2020.105831

Cited by 7 publications

(2 citation statements)

References 19 publications

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“…The scheme considers terminal constraints, and the guidance law modifies the lift coefficient by applying constraints on load factor and dynamic pressure. Assessment of robust stability of an autonomous lander using a methodology employing mu-Analysis and Monte Carlo simulations are implemented [16]. This technique is applied to a case study representing a descent module during the controlled landing phase on the Mars surface.…”

Section: Introductionmentioning

confidence: 99%

Approach and landing guidance using constrained model predictive static programming

Hameed,

G．R．,

Vutukuri

2024

Aerospace Science and Technology

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Section: Introductionmentioning

confidence: 99%

Approach and landing guidance using constrained model predictive static programming

Hameed,

G．R．,

Vutukuri

2024

Aerospace Science and Technology

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“…With the success of a series of planetary exploration missions, researchers' understanding of the planetary characteristics and planetary landing is more and more in depth [1,2], and more appropriate potential landing target points will be found [3]. Due to the uncertain planetary environmental factors and possible faults of the lander [4,5], the actual trajectory may deviate from the preset trajectory or even make the origin landing point unreachable. At this time, how to rapidly determine the reachable landing points from potential landing target points and plan the trajectory online brings new challenges for powered descent guidance algorithms.…”

Section: Introductionmentioning

confidence: 99%

Semi-Analytical Planetary Landing Guidance with Constraint Equations Using Model Predictive Control

et al. 2022

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With the deepening of planetary exploration, rapid decision making and descent trajectory planning capabilities are needed to cope with uncertain environmental disturbances and possible faults during planetary landings. In this article, a novel decoupling method is adopted, and the analytical three-dimensional constraint equations are derived and solved, ensuring real-time guidance computation. The three-dimensional motion modes and thrust profiles are analyzed and determined based on Pontryagin’s minimum principle, and a supporting semi-analytical reachability judgment method is presented, which can also be used to determine controllability. The algorithm is embedded in the model predictive control (MPC) framework, and several techniques are adopted to enhance stability and robustness, including thrust averaging, thrust correction after ignition, thrust reservation, and open-loop terminal guidance. Numerical simulations demonstrate that the proposed algorithm can guarantee real-time trajectory generation and meanwhile maintain considerable optimality. In addition, the MPC simulation shows that the algorithm can maintain a good accuracy under external disturbances.

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Powered soft landing guidance method for launchers with non-cluster configured engines

Song

Cong

2021

Acta Astronautica

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GNC robustness stability verification for an autonomous lander

Cited by 7 publications

References 19 publications

Approach and landing guidance using constrained model predictive static programming

Approach and landing guidance using constrained model predictive static programming

Semi-Analytical Planetary Landing Guidance with Constraint Equations Using Model Predictive Control

Powered soft landing guidance method for launchers with non-cluster configured engines

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