Long-Term Station Keeping of Space Station in Lunar Halo Orbits

Ulybyshev, Yuri

doi:10.2514/1.g000242

Cited by 20 publications

(12 citation statements)

References 18 publications

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“…where µ i is the gravitational constants for any of the planets considered in the model, while r i is the position vector for that planet. An example of this model is used in [59], which considers the solar radiation pressure as the perturbed acceleration. Other forms of equations describing the dynamics of Lagrange's points vary for different coordinate systems and expected accuracies.…”

Section: Libration Pointsmentioning

confidence: 99%

“…Other forms of cost functions for acceleration are popular in spacecraft trajectory optimization problems, specifically in shape-based techniques [101]. The reason is that in these researches, the state vectors are directly interpolated via polynomials with discretization [59]. So the acceleration (similarly the thrust magnitude) will be achieved as a function of optimization variables.…”

Section: Accelerationmentioning

confidence: 99%

See 1 more Smart Citation

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions

Shirazi

Ceberio

Lozano

2018

Progress in Aerospace Sciences

124

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This article is a survey paper on solving spacecraft trajectory optimization problems. The solving process is decomposed into four key steps of mathematical modeling of the problem, defining the objective functions, development of an approach and obtaining the solution of the problem. Several subcategories for each step have been identified and described. Subsequently, important classifications and their characteristics have been discussed for solving the problems. Finally, a discussion on how to choose an element of each step for a given problem is provided.

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Section: Libration Pointsmentioning

confidence: 99%

Section: Accelerationmentioning

confidence: 99%

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions

Shirazi

Ceberio

Lozano

2018

Progress in Aerospace Sciences

124

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“…The results obtained were verified by the LQR method. More recently, Ulybyshev 21 presented his work about the long-term stationkeeping in the Earth-Moon vicinity. Folta et al 22 and Pavlak and Howell 23 compared two promising stationkeeping strategies for the ARTEMIS mission.…”

Section: Introductionmentioning

confidence: 99%

“…The results obtained were verified by the LQR method. More recently, Ulybyshev 21 presented his work about the long-term stationkeeping in the Earth-Moon vicinity. Folta et al.…”

Section: Introductionmentioning

confidence: 99%

Stationkeeping strategy for quasi-periodic orbit around Earth–Moon L₂ point

Qian

Liu²,

Zhang

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part G:

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Quasi-periodic orbits in the Earth-Moon system are highly sensitive and even small errors in position and/or velocity have strong influence on the trajectory. These types of trajectories are unstable and must be controlled to maintain the corresponding orbits. This paper investigates the stationkeeping strategy for quasi-periodic orbits near the translunar libration point with full consideration of the contribution from the Sun's gravity and the Moon's eccentricity, in which the continuous low-thrust is preformed to enforce the probe following several onboard decided target points on the baseline. A new high-fidelity model is derived to describe motions of the quasi-periodic orbits by using the standard ephemerides. Based on the improved multiple-shooting method and the proposed model, a baseline trajectory is obtained. Then, a new continuous low-thrust-based stationkeeping strategy is proposed. Specifically, by employing Gauss pseudospectral method in the stationkeeping algorithm and by introducing the maximal excursion and fixed time interval, the target points on the baseline trajectory are chosen onboard based on real-time data. Simulation results show that the unstable quasi-periodic orbit can be maintained effectively with the low-energy consumption.

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“…In this respect, several control design methods have been proposed throughout the last decades for stabilizing Halo orbits while mitigating the effect of perturbations and unmodelled dynamics (see [11] for a complete survey, and [12] for an earlier work). Among these and related to this work, the most important ones are based on optimization [13][14][15][16][17][18][19], receding horizon [20,21] and advanced nonlinear design (e.g. projection to the stable manifold [22], feedback linearization, nonlinear regulation [23] and backstepping [24]).…”

Section: Introductionmentioning

confidence: 99%

Station-keeping of $L_2$ halo orbits under sampled-data model predictive control

Elobaid¹,

Mattioni²,

Monaco³

et al. 2022

Preprint

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the digital nature of both actuation and sensing and possible limits on control, unavoidable in practice. In particular, we consider the case in which measures are available only at sporadic time instants whereas the control is piecewise constant over the sampling period (e.g. [25]). The approach we propose is based on the design of multi-rate (MR) strategies at the planning level providing a suitable reference governor for a model-predictive control (MPC) control scheme. The resulting control system enables to overcome the limits of small prediction horizons underlined in [21], when the controller is designed under usual MPC. As a matter of fact, such limits would bring to unfeasible controllers for small prediction horizons when the design makes use of a the sampled-data model, due to the cancellation of the possibly unstable zero-dynamics under sampling [26]. Also, the use of large prediction horizons, typically used as a stratagem in practice, might introduce large computational delays.This work is contextualized in this framework by proposing a new sampled-data MPC control scheme where the problem is simplified. This is achieved by generating a suitable reference trajectory based on a multi-rate planner which guarantees stability of the closed loop and feasibility of the optimization problem solved, at each step, by the MPC assuming cheap control. In particular, such a planner is designed starting from the nonlinear regulation-based controller proposed in [23] which yields, by construction, admissible and bounded trajectories which can be then fed to the MPC as reference to track. In this context, the contribution of this paper stands in the proposition of a new control scheme which employs at the low level an inherently robust nonlinear MPC fed by a references generated by a multi-rate sampled-data model of a control system designed making use of nonlinear regulation.The choice of the proposed control scheme is motivated by the observation that MPC and nonlinear regulation can be employed together to mitigate each the deficiencies of the other: nonlinear regulation appears to be the natural context for setting the problem since the references and perturbations are periodic although it lacks in robustness to unmodelled disturbances; MPC is becoming a standard tool for handling tracking applications, it is inherently robust to bounded perturbations [27] despite it requiring reference signals pre-processing to guarantee convergence and recursive feasibility.

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Long-Term Station Keeping of Space Station in Lunar Halo Orbits

Cited by 20 publications

References 18 publications

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions

Stationkeeping strategy for quasi-periodic orbit around Earth–Moon L₂ point

Station-keeping of $L_2$ halo orbits under sampled-data model predictive control

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Long-Term Station Keeping of Space Station in Lunar Halo Orbits

Cited by 20 publications

References 18 publications

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions

Stationkeeping strategy for quasi-periodic orbit around Earth–Moon L2 point

Station-keeping of $L_2$ halo orbits under sampled-data model predictive control

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Stationkeeping strategy for quasi-periodic orbit around Earth–Moon L₂ point