A New Algorithm to Generate Low-thrust Spacecraft Trajectories
A New Algorithm to Generate Low-thrust Spacecraft Trajectories

Author: Suwat Sreesawet

Publisher:

Published: 2014

Total Pages: 54

ISBN-13:

DOWNLOAD EBOOK

All-electric satellites are gaining favor among the manufacturers and operators of satellites in Geostationary Earth Orbit (GEO) due to cost saving potential. These satellites have the capability of performing all propulsive tasks with electric propulsion including transfer to GEO. Although fuel-efficient, electric thrusters lead to long transfer, during which the health and the usability of spacecraft is affected due to its exposure to hazardous space radiation in the Van Allen belts. Hence, determining electric orbit-raising trajectory that minimize transfer time is crucial for all-electric satellite operation. This thesis proposes a novel method to determine minimum-time orbit-raising trajectory by blending the ideas of direct optimization and guidance-like trajectory optimization schemes. The proposed methodology is applicable for both planar and non-planar transfers and for transfers starting from arbitrary circular and elliptic orbits. Therefore, it can be used for rapidly analyzing various orbit-raising mission scenarios. The methodology utilizes the variational equations of motion of the satellite in the context of the two-body problem by considering the low-thrust of an electric engine as a perturbing force. The no-thrust condition due to Earth's shadow is also considered. The proposed methodology breaks the overall optimization problem into multiple sub-problems and each sub-problem minimizes a desired objective over the sun-lit part of the trajectory. Two different objective types are considered. Type I transfers minimize the deviation of the total energy and eccentricity of final position from the GEO, while type II transfers minimize the deviation of total energy and angular momentum. Using the developed tool, several mission scenarios are analyzed including, a new type of mission scenarios, in which more than one thruster type are used for the transfer. The thesis presents the result for all studied scenarios and compares the performance of Type I and Type II transfers.

Optimization of Low Thrust Spacecraft Trajectories Using a Genetic Algorithm
Optimization of Low Thrust Spacecraft Trajectories Using a Genetic Algorithm

Author: Jason Corey Eisenreich

Publisher:

Published: 1998-01-01

Total Pages: 79

ISBN-13: 9781423554493

DOWNLOAD EBOOK

This thesis concerns the use of genetic algorithms in the optimization of the trajectories of low thrust spacecraft. Genetic algorithms are programming tools which use the principles of biological evolution and adaptation to optimize processes. These algorithms have been found to be very useful in many different engineering disciplines. The goal of this project is to determine their applicability to the generation and optimization of low thrust spacecraft trajectories. This thesis describes the basic operating principles of genetic algorithms and then applies them to two different missions.

A Trajectory Generation and System Characterization Model for Cislunar Low-Thrust Spacecraft. Volume 2
A Trajectory Generation and System Characterization Model for Cislunar Low-Thrust Spacecraft. Volume 2

Author: National Aeronautics and Space Administration (NASA)

Publisher: Createspace Independent Publishing Platform

Published: 2018-07-06

Total Pages: 66

ISBN-13: 9781722150853

DOWNLOAD EBOOK

The documentation of the Trajectory Generation and System Characterization Model for the Cislunar Low-Thrust Spacecraft is presented in Technical and User's Manuals. The system characteristics and trajectories of low thrust nuclear electric propulsion spacecraft can be generated through the use of multiple system technology models coupled with a high fidelity trajectory generation routine. The Earth to Moon trajectories utilize near Earth orbital plane alignment, midcourse control dependent upon the spacecraft's Jacobian constant, and capture to target orbit utilizing velocity matching algorithms. The trajectory generation is performed in a perturbed two-body equinoctial formulation and the restricted three-body formulation. A single control is determined by the user for the interactive midcourse portion of the trajectory. The full spacecraft system characteristics and trajectory are provided as output. Korsmeyer, David J. and Pinon, Elfego, III and Oconnor, Brendan M. and Bilby, Curt R. Unspecified Center...

A Reinforcement Learning Approach to Spacecraft Trajectory Optimization
A Reinforcement Learning Approach to Spacecraft Trajectory Optimization

Author: Daniel S. Kolosa

Publisher:

Published: 2019

Total Pages: 69

ISBN-13:

DOWNLOAD EBOOK

This dissertation explores a novel method of solving low-thrust spacecraft targeting problems using reinforcement learning. A reinforcement learning algorithm based on Deep Deterministic Policy Gradients was developed to solve low-thrust trajectory optimization problems. The algorithm consists of two neural networks, an actor network and a critic network. The actor approximates a thrust magnitude given the current spacecraft state expressed as a set of orbital elements. The critic network evaluates the action taken by the actor based on the state and action taken. Three different types of trajectory problems were solved, a generalized orbit change maneuver, a semimajor axis change maneuver, and an inclination change maneuver. When training the algorithm in a simulated space environment, it was able to solve both the generalized orbit change and semimajor axis change maneuvers with no prior knowledge of the environment’s dynamics. The robustness of the algorithm was tested on an inclination change maneuver with a randomized set of initial states. After training, the algorithm was able to successfully generalize and solve new inclination changes that it has not seen before. This method has potential future applications in developing more complex low-thrust maneuvers or real-time autonomous spaceflight control.

Spacecraft Trajectory Optimization
Spacecraft Trajectory Optimization

Author: Bruce A. Conway

Publisher: Cambridge University Press

Published: 2010-08-23

Total Pages: 313

ISBN-13: 113949077X

DOWNLOAD EBOOK

This is a long-overdue volume dedicated to space trajectory optimization. Interest in the subject has grown, as space missions of increasing levels of sophistication, complexity, and scientific return - hardly imaginable in the 1960s - have been designed and flown. Although the basic tools of optimization theory remain an accepted canon, there has been a revolution in the manner in which they are applied and in the development of numerical optimization. This volume purposely includes a variety of both analytical and numerical approaches to trajectory optimization. The choice of authors has been guided by the editor's intention to assemble the most expert and active researchers in the various specialities presented. The authors were given considerable freedom to choose their subjects, and although this may yield a somewhat eclectic volume, it also yields chapters written with palpable enthusiasm and relevance to contemporary problems.

An Efficient Algorithm for Computing the Low-thrust Escape Trajectory
An Efficient Algorithm for Computing the Low-thrust Escape Trajectory

Author: John A. Gall

Publisher:

Published: 2004

Total Pages: 122

ISBN-13:

DOWNLOAD EBOOK

An algorithm to improve the computational efficiency of the low-thrust escape trajectory is developed. The algorithm reduces computational effort while maintaining accuracy, making it desirable for use in computing optimal escape trajectory by direct method. As low-thrust ionic propulsion engines are considered for use in interplanetary missions, design and planning includes the optimization of the spacecraft trajectory. The low-thrust escape phase evolves in the form of a slowly unwinding spiral. The computational expense required to accurately propagate the dense spiraling trajectory of the planetocentric escape phase through the numerical integration of the ordinary differential equations is undesirable. Implementation of an algorithm that approximates the trajectory while maintaining accuracy and improving computational efficiency is beneficial. The algorithm developed is demonstrated with the optimization of a sample Earth-escape trajectory. An inexpensive trajectory calculation with little error is produced.

Low-thrust Spacecraft Guidance and Control Using Proximal Policy Optimization
Low-thrust Spacecraft Guidance and Control Using Proximal Policy Optimization

Author: Daniel Martin Miller

Publisher:

Published: 2020

Total Pages: 107

ISBN-13:

DOWNLOAD EBOOK

Artificial intelligence is a rapidly developing field that promises to revolutionize spaceflight with greater robotic autonomy and innovative decision making. However, it remains to be determined which applications are best addressed using this new technology. In the coming decades, future spacecraft will be required to possess autonomous guidance and control in the complex, nonlinear dynamical regimes of cis-lunar space. In the realm of trajectory design, current methods struggle with local minima, and searching large solutions spaces. This thesis investigates the use of the Reinforcement Learning (RL) algorithm Proximal Policy Optimization (PPO) for solving low-thrust spacecraft guidance and control problems. First, an agent is trained to complete a 302 day mass-optimal low-thrust transfer between the Earth and Mars. This is accomplished while only providing the agent with information regarding its own state and that of Mars. By comparing these results to those generated by the Evolutionary Mission Trajectory Generator (EMTG), the optimality of the trajectory designed using PPO is assessed. Next, an agent is trained as an onboard regulator capable of correcting state errors and following pre-calculated transfers between libration point orbits. The feasibility of this method is examined by evaluating the agent’s ability to correct varying levels of initial state error via Monte Carlo testing. The generalizability of the agent’s control solution is appraised on three similar transfers of increasing difficulty not seen during the training process. The results show both the promise of the proposed PPO methodology and its limitations, which are discussed.

Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems

Author: Runqi Chai

Publisher: Springer

Published: 2019-07-30

Total Pages: 207

ISBN-13: 9811398453

DOWNLOAD EBOOK

This book explores the design of optimal trajectories for space maneuver vehicles (SMVs) using optimal control-based techniques. It begins with a comprehensive introduction to and overview of three main approaches to trajectory optimization, and subsequently focuses on the design of a novel hybrid optimization strategy that combines an initial guess generator with an improved gradient-based inner optimizer. Further, it highlights the development of multi-objective spacecraft trajectory optimization problems, with a particular focus on multi-objective transcription methods and multi-objective evolutionary algorithms. In its final sections, the book studies spacecraft flight scenarios with noise-perturbed dynamics and probabilistic constraints, and designs and validates new chance-constrained optimal control frameworks. The comprehensive and systematic treatment of practical issues in spacecraft trajectory optimization is one of the book’s major features, making it particularly suited for readers who are seeking practical solutions in spacecraft trajectory optimization. It offers a valuable asset for researchers, engineers, and graduate students in GNC systems, engineering optimization, applied optimal control theory, etc.