An investigation of the applicability of genetic algorithms to spacecraft trajectory optimization
Author: Elfego Piñon
Publisher:
Published: 1995
Total Pages: 366
ISBN-13:
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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 EBOOKThis 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.
Genetic Algorithms for Aeroassisted Trajectory Optimization and Time-optimal Spacecraft Reorientation Controller Design
Author: Yao-Feng Cheng
Publisher:
Published: 1994
Total Pages: 232
ISBN-13:
DOWNLOAD EBOOK"An algorithm based on the mechanics of natural genetics is used to solve two different optimization problems. The algorithm combines survival of the fittest among string structures with randomized information exchange to form a search algorithm. Initiated with a population of bits-coded individuals, the genetic algorithm searches for the optimal solutions generation-by-generation. The three main operations in the genetic algorithm: Reproduction, Crossover, and Mutation give this algorithm the power of searching. In the first part of this thesis, the genetic algorithm is used to determine the optimal trajectories of the aeroassisted vehicle reentry problem. The trajectories to be optimized are determined not only by the parameter searching but also under a height constraint which make this study more interesting. In the second part of this thesis the genetic algorithm is used for designing three-axis bang-bang controllers for the time-optimal rigid spacecraft reorientation problem. The firing times of the bang-bang controller and the time of rotation are determined by searching for the angular velocity thresholds and the reorientation time"--Abstract, leaf iv.
Genetic Algorithms and Engineering Optimization
Author: Mitsuo Gen
Publisher: John Wiley & Sons
Published: 1999-12-28
Total Pages: 520
ISBN-13: 9780471315315
DOWNLOAD EBOOKIm Mittelpunkt dieses Buches steht eines der wichtigsten Optimierungsverfahren der industriellen Ingenieurtechnik: Mit Hilfe genetischer Algorithmen lassen sich Qualität, Design und Zuverlässigkeit von Produkten entscheidend verbessern. Das Verfahren beruht auf der Wahrscheinlichkeitstheorie und lehnt sich an die Prinzipien der biologischen Vererbung an: Die Eigenschaften des Produkts werden, unter Beachtung der äußeren Randbedingungen, schrittweise optimiert. Ein hochaktueller Band international anerkannter Autoren. (03/00)
Advanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles
Author: Runqi Chai
Publisher: Springer Nature
Published: 2023-10-29
Total Pages: 272
ISBN-13: 9819943116
DOWNLOAD EBOOKThis book focuses on the design and application of advanced trajectory optimization and guidance and control (G&C) techniques for aerospace vehicles. Part I of the book focuses on the introduction of constrained aerospace vehicle trajectory optimization problems, with particular emphasis on the design of high-fidelity trajectory optimization methods, heuristic optimization-based strategies, and fast convexification-based algorithms. In Part II, various optimization theory/artificial intelligence (AI)-based methods are constructed and presented, including dynamic programming-based methods, model predictive control-based methods, and deep neural network-based algorithms. Key aspects of the application of these approaches, such as their main advantages and inherent challenges, are detailed and discussed. Some practical implementation considerations are then summarized, together with a number of future research topics. The comprehensive and systematic treatment of practical issues in aerospace trajectory optimization and guidance and control problems is one of the main features of the book, which is particularly suitable for readers interested in learning practical solutions in aerospace trajectory optimization and guidance and control. The book is useful to researchers, engineers, and graduate students in the fields of G&C systems, engineering optimization, applied optimal control theory, etc.
Industrial Applications of Genetic Algorithms
Author: Charles Karr
Publisher: CRC Press
Published: 1998-12-29
Total Pages: 360
ISBN-13: 9780849398018
DOWNLOAD EBOOKGenetic algorithms (GAs) are computer-based search techniques patterned after the genetic mechanisms of biological organisms that have adapted and flourished in changing, highly competitive environments for millions of years. GAs have been successfully applied to problems in a variety of studies, and their popularity continues to increase because of their effectiveness, applicability, and ease of use. Industrial Applications of Genetic Algorithms shows how GAs have made the leap form their origins in the laboratory to the practicing engineer's toolbox. Each chapter in the book describes a project completed by a graduate student at the University of Alabama.
An Overview of Evolutionary Algorithms Toward Spacecraft Attitude Control
Author: Matthew Cooper
Publisher:
Published: 2019
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKEvolutionary algorithms can be used to solve interesting problems for aeronautical and astronautical applications, and it is a must to review the fundamentals of the most common evolutionary algorithms being used for those applications. Genetic algorithms, particle swarm optimization, firefly algorithm, ant colony optimization, artificial bee colony optimization, and the cuckoo search algorithm are presented and discussed with an emphasis on astronautical applications. In summary, the genetic algorithm and its variants can be used for a large parameter space but is more efficient in global optimization using a smaller chromosome size such that the number of parameters being optimized simultaneously is less than 1000. It is found that PID controller parameters, nonlinear parameter identification, and trajectory optimization are applications ripe for the genetic algorithm. Ant colony optimization and artificial bee colony optimization are optimization routines more suited for combinatorics, such as with trajectory optimization, path planning, scheduling, and spacecraft load bearing. Particle swarm optimization, firefly algorithm, and cuckoo search algorithms are best suited for large parameter spaces due to the decrease in computation need and function calls when compared to the genetic algorithm family of optimizers. Key areas of investigation for these social evolution algorithms are in spacecraft trajectory planning and in parameter identification.
System Architecture Optimization Using Hidden Genes Genetic Algorithms with Applications in Space Trajectory Optimization
Author:
Publisher:
Published: 2018
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAbstract : In this dissertation, the concept of hidden genes genetic algorithms is developed. In system architecture optimization problems, the topology of the solution is unknown and hence, the number of design variables is variable. Hidden genes genetic algorithms are genetic algorithm based methods that are developed to handle such problems by hiding some genes in the chromosomes. The genes in the hidden genes genetic algorithms evolve through selection, mutation, and crossover operations. To determine if a gene is hidden or not, binary tags are assigned to them. The value of the tags determine the status of the genes. Different mechanisms are proposed for the evolution of the tags. Some mechanisms utilize stochastic operations while others are based on deterministic operations. All the proposed mechanisms are tested on mathematical and space trajectory optimization problems. Moreover, Markov chain models of the mechanisms are derived and their convergence is investigated analytically. The results show that the proposed concept are capable to search for the optimal solution by autonomously enabling the algorithms to assign the hidden genes.
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 EBOOKThis 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.
Evolutionary Algorithms Applied to Interplanetary Spacecraft Trajectories Optimization
Author: Daniel Ramírez Parejo
Publisher:
Published: 2018
Total Pages:
ISBN-13:
DOWNLOAD EBOOKSending spacecrafts to any other planet or satellite within the Solar System is a difficult task. To be able to reach it at a precise time, it is crucial to know at which position the target planet is going to be, as well as a good study of the trajectory that the spacecraft is going to follow, which shall not be too close to any other object in the Solar System. It must be also be taken into account that the spacecrafts have a limited fuel capacity. In order to avoid using a high amount of fuel, multi-gravity assist trajectories are useful to provide additional manoeuvering to the spacecrafts without consuming fuel. Given an arbitrary sequence of planets for the swing-by manoeuvres, the next step is to determine when the spacecraft must be launched and how long will it take to it to perform the transfer trajectory. In this preliminary stage of the mission analy-sis, optimization algorithms can be used to obtain the most efficient trajectory, for instance, the trajectory at which the spacecraft requires the least amount of fuel to reach its destination. From the wide variety of heuristic optimization algorithms, in this Master's thesis four of them have been chosen (Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Algorithm and the simulated annealing algorithm). The aim of this thesis is to perform a hyperparameter optimization, that is, finding whether a certain combination of parameters for each optimizer works properly for different trajecto-ries' scenarios: a direct launch to an outer planet and a multi-gravity assist scenario to outer planets as well as to inner planets. The results show that it exists a region of parameters for the Genetic Algorithm and the Differential Evolution Algorithm where the best solutions can be found. Simulated Annealing Algorithm shows a dependance on the scenario, as well as some parameters of the Particle Swarm Algorithm.
