651 research outputs found
Preliminary capture trajectory design for Europa tomography probe
The objective of this work is the preliminary design of a low-DV transfer from an initial elliptical orbit around Jupiter into a final circular orbit around the moon Europa. This type of trajectory represents an excellent opportunity for a low-cost mission to Europa, accomplished through a small orbiter, as in the proposed Europa Tomography Probe mission, a European contribution to NASA’s Europa Multiple-Flyby Mission (or Europa Clipper). The mission strategy is based on the v-infinity leveraging concept, and the use of resonant orbits to exploit multiple gravity-assist from the moon. Possible sequences of resonant orbits are selected with the help of the Tisserand graph. Suitable trajectories are provided by an optimization code based on the parallel running of several differential evolution algorithms. Different solutions are finally compared in terms of propellant consumption and flight time
Optimal Trajectories for Near-Earth-Objects Using Solar Electric Propulsion (SEP) and Gravity Assisted Maneuver
The future interplanetary missions will probably use the conventional chemical rockets to leave the sphere of influence of the Earth, and solar electric propulsion (SEP) to accomplish the other maneuvers of the mission. In this work the optimization of interplanetary missions using solar electric propulsion and Gravity Assisted Maneuver to reduce the costs of the mission, is considered. The high specific impulse of electric propulsion makes a Gravity Assisted Maneuver 1 year after departure convenient. Missions for several Near Earth Asteroids will be considered. The analysis suggests criteria for the definition of initial solutions demanded for the process of optimization of trajectories. Trajectories for the asteroid 2002TC70 are analyzed. Direct trajectories, trajectories with 1 gravity assisted from the Earth and with 2 gravity assisted from the Earth and either Mars are present. An indirect optimization method will be used in the simulations
Indirect Optimization of Satellite Deployment into a Highly Elliptic Orbit
The analysis of the optimal strategies for the deployment of a spacecraft into a highly elliptic orbit is carried out by means of an indirect optimization procedure, which is based on the theory of optimal control. The orbit peculiarities require that several perturbations are taken into account: an 8x8 model of the Earth's potential is adopted and gravitational perturbations from Moon and Sun together with solar radiation pressure are considered. A procedure to guarantee convergence and define the optimal switching structure is outlined. Results concerning mission with up to 4.5 revolutions around the Earth are given and significant features of this kind of deployment are highlighte
Autonomous Upper Stage Guidance with Robust Splash-Down Constraint
This paper presents a novel algorithm, based on model predictive control
(MPC), for the optimal guidance of a launch vehicle upper stage. The proposed
strategy not only maximizes the performance of the vehicle and its robustness
to external disturbances, but also robustly enforces the splash-down
constraint. Indeed, uncertainty on the engine performance, and in particular on
the burn time, could lead to a large footprint of possible impact points, which
may pose a concern if the reentry points are close to inhabited regions. Thus,
the proposed guidance strategy incorporates a neutral axis maneuver (NAM) that
minimizes the sensitivity of the impact point to uncertain engine performance.
Unlike traditional methods to design a NAM, which are particularly burdensome
and require long validation and verification tasks, the presented MPC algorithm
autonomously determines the neutral axis direction by repeatedly solving an
optimal control problem (OCP) with two return phases, a nominal and a perturbed
one, constrained to the same splash-down point. The OCP is transcribed as a
sequence of convex problems that quickly converges to the optimal solution,
thus allowing for high MPC update frequencies. Numerical results assess the
robustness and performance of the proposed algorithm via extensive Monte Carlo
campaigns.Comment: arXiv admin note: text overlap with arXiv:2210.1461
GTOC X: Solution Approach of Team Sapienza-PoliTo
This paper summarizes the solution approach and the numerical methods developed by the joint team Sapienza University of Rome and Politecnico di Torino (Team Sapienza-PoliTo) in the context of the 10th Global Trajectory Optimization Competition. The proposed method is based on a preliminary partition of the galaxy into several small zones of interest, where partial settlement trees are developed, in order to match a (theoretical) optimal star distribution. A multi-settler stochastic Beam Best-First Search, that exploits a guided multi-star multi-vessel transition logic, is proposed for solving a coverage problem, where the number of stars to capture and their distribution within a zone is assigned. The star-to-star transfers were then optimized through an indirect procedure. A number of refinements, involving settle time re-optimization, explosion, and pruning, were also investigated. The submitted 1013-star solution, as well as an enhanced 1200-point rework, are presented
Convex Optimization of Launch Vehicle Ascent Trajectory with Heat-Flux and Splash-Down Constraints
This paper presents a convex programming approach to the optimization of a
multistage launch vehicle ascent trajectory, from the liftoff to the payload
injection into the target orbit, taking into account multiple nonconvex
constraints, such as the maximum heat flux after fairing jettisoning and the
splash-down of the burned-out stages. Lossless and successive convexification
are employed to convert the problem into a sequence of convex subproblems.
Virtual controls and buffer zones are included to ensure the recursive
feasibility of the process and a state-of-the-art method for updating the
reference solution is implemented to filter out undesired phenomena that may
hinder convergence. A hp pseudospectral discretization scheme is used to
accurately capture the complex ascent and return dynamics with a limited
computational effort. The convergence properties, computational efficiency, and
robustness of the algorithm are discussed on the basis of numerical results.
The ascent of the VEGA launch vehicle toward a polar orbit is used as case
study to discuss the interaction between the heat flux and splash-down
constraints. Finally, a sensitivity analysis of the launch vehicle carrying
capacity to different splash-down locations is presented.Comment: 2020 AAS/AIAA Astrodynamics Specialist Virtual Lake Tahoe Conferenc
Stochastic Control of Launch Vehicle Upper Stage with Minimum-Variance Splash-Down
This paper presents a novel synthesis method for designing an optimal and
robust guidance law for a non-throttleable upper stage of a launch vehicle,
using a convex approach. In the unperturbed scenario, a combination of lossless
and successive convexification techniques is employed to formulate the guidance
problem as a sequence of convex problems that yields the optimal trajectory, to
be used as a reference for the design of a feedback controller, with little
computational effort. Then, based on the reference state and control, a
stochastic optimal control problem is defined to find a closed-loop control law
that rejects random in-flight disturbance. The control is parameterized as a
multiplicative feedback law; thus, only the control direction is regulated,
while the magnitude corresponds to the nominal one, enabling its use for solid
rocket motors. The objective of the optimization is to minimize the splash-down
dispersion to ensure that the spent stage falls as close as possible to the
nominal point. Thanks to an original convexification strategy, the stochastic
optimal control problem can be solved in polynomial time since it reduces to a
semidefinite programming problem. Numerical results assess the robustness of
the stochastic controller and compare its performance with a model predictive
control algorithm via extensive Monte Carlo campaigns
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