Critical aspects of spacecraft missions, such as component organization, control algorithms, and trajectories, can be optimized using a variety of algorithms or solvers. Each solver has intrinsic strengths and weaknesses when applied to a given optimization problem. One way to mitigate limitations is to combine different solvers in an island model that allows these algorithms to share solutions. The program Spacecraft Trajectory Optimization Suite (STOpS) is an island model suite of heterogeneous and homogeneous Evolutionary Algorithms (EA) that analyze interplanetary trajectories for multiple gravity assist (MGA) missions. One limitation of STOpS and other spacecraft trajectory optimization programs (GMAT and Pygmo/Pagmo) is that they require a defined encounter body sequence to produce a constant length set of design variables. Early phase trajectory design would benefit from the ability to consider problems with an undefined encounter sequence as it would provide a set of diverse trajectories -- some of which might not have been considered during mission planning. The Hybrid Optimal Control Problem (HOCP) and the concept of hidden genes are explored with the most common EA, the Genetic Algorithm (GA), to compare how the methods perform with a Variable Size Design Space (VSDS). Test problems are altered so that the input to the cost function (the object being optimized) contains a set of continuous variables whose length depends on a corresponding set of discrete variables (e.g. the number of planet encounters determines the number of transfer time variables). Initial testing with a scalable problem (Branin's function) indicates that even though the HOCP consistently converges on an optimal solution, the expensive run time (due to algorithm collaboration) would only escalate in an island model system. The hidden gene mechanism only changes how the GA decodes variables, thus it does not impact run time and operates effectively in the island model. A Hidden Gene Genetic Algorithm ( HGGA) is tested with a simplified Mariner 10 (EVM) problem to determine the best parameter settings to use in an island model with the GTOP Cassini 1 (EVVEJS) problem. For an island model with all GAs there is improved performance when the different base algorithm settings are used. Similar to previous work, the model benefits from migration of solutions and using multiple algorithms or islands. For spacecraft trajectory optimization programs that have an unconstrained fly-by sequence, the design variable limits have the largest impact on the results. When the number of potential fly-by sequences is too large it prevents the solver from converging on an optimal solution. This work demonstrates HGGA is effective in the STOpS environment as well as with GTOP problems. Thus the hidden gene mechanism can be extended to other EAs with members containing design variables that function similarly. It is shown that the tuning of the HGGA is dependent on the specific constraints of the spacecraft trajectory problem at hand, thus there is no need to further explore the general capabilities of the algorithm.

In October 2017, the first interstellar object, designated 1I/2017 U1 and more commonly referred to as Oumuamua, was detected passing through our solar system by the Pan-STARRS telescope, followed recently by the detection of 2I/Borisov in August 2019. These detections came much sooner than thought possible, and have redefined our understanding of the population of interstellar objects. With the construction of the next generation of powerful observatories, future detections are estimated to occur as frequently as two per year, and while there is significant scientific understanding to be gained from observing these objects remotely, a spacecraft sent to intercept one might be the only way to collect up-close, detailed information on the composition of extra solar object. The ideal mission scenario would be a combination flyby and impact as performed and proven feasible by the Deep Impact encounter with the comet Temple 1. A study has already been done showing that trajectories to interstellar objects are feasible with current chemical propulsion and a “launch on detection” paradigm, with an estimated 10 year wait time between favorable mission opportunities, assuming future detection capabilities. However, while a trajectory to one of these objects might be feasible, accurately performing a flyby and impacting an object with a hyperbolic orbit presents unprecedented navigational challenges. Spacecraft-target relative velocities can range between 10 km/s to 110 km/s with high phase angles between 90° and 180°. The goal of this thesis is to determine the required navigation hardware – an optical navigation camera and attitude determination system – which could provide high mission success probability for many potential encounter scenarios. This work is performed via a simulation program developed at the Jet Propulsion Laboratory that generates simulated images of a target during the terminal guidance phase of a mission, and feeds them into the algorithms behind autonomous navigation software (AutoNav) used for the Deep Impact mission. Observations are derived from the images and used to perform target-relative orbit determination and calculate correction maneuvers.

We consider two models which lead to the prediction of a weight change of gyroscopes depending on the rate of rotation: mass-energy equivalence and Weber's force for gravitation. We calculate the order of magnitude of this effect in both models and show that Weber's model predicts a weight change depending on the spin axis orientation resembling close similarities to observed Earth flyby anomalies. however, our predicted effect is much smaller than the observed effect, which could explain why flyby anomalies were not detected anymore in recent spracecraft trajectories.

We consider two models which lead to the prediction of a weight change of gyroscopes depending on the rate of rotation: mass-energy equivalence and Weber's force for gravitation. We calculate the order of magnitude of this effect in both models and show that Weber's model predicts a weight change depending on the spin axis orientation resembling close similarities to observed Earth flyby anomalies. however, our predicted effect is much smaller than the observed effect, which could explain why flyby anomalies were not detected anymore in recent spracecraft trajectories.

One of the most important aspects of preliminary interplanetary mission planning entails designing a trajectory that delivers a spacecraft to the required destinations and accomplishes all the objectives. The design tool described in this thesis allows an investigator to explore various interplanetary trajectories quickly and easily. The design tool employs the patched conic method to determine heliocentric and planetocentric trajectory information. An existing Lambert Targeting routine and other common algorithms are utilized in conjunction with the design tool’s specialized code to formulate an entire trajectory from Earth departure to arrival at the destination. The tool includes many options for the investigator to accurately configure the desired trajectory, including planetary gravity assists, deep space maneuvers, and various departure and arrival conditions. The trajectory design tool is coded in MATLAB, which provides access to three dimensional plotting options and user adaptability. The design tool also incorporates powerful MATLAB optimization functions that adjust trajectory characteristics to find a configuration that yields the minimum spacecraft propellant in the form of change in velocity. / text

Preliminary interplanetary trajectory designs frequently use simplified two-body orbital mechanics and linked conics methodology to model the complex trajectories in multi-body systems. Incorporating gravity assists provides highly efficient interplanetary trajectories, enabling otherwise infeasible spacecraft missions. Future missions may employ powered gravity assists, using a propulsive maneuver during the flyby, improving the overall trajectory performance. This dissertation provides a complete description and analysis of a new interplanetary trajectory design tool known as TRACT (TRAjectory Configuration Tool). TRACT is capable of modeling complex interplanetary trajectories, including multiple ballistic and/or powered gravity assists, deep space maneuvers, parking orbits, and other common maneuvers. TRACT utilizes an adaptable architecture of modular boundary value problem (BVP) algorithms for all trajectory segments. A bi-level optimization scheme is employed to reduce the number of optimization variables, simplifying the user provided trajectory information. The standardized optimization parameter set allows for easy use of TRACT with a variety of optimization algorithms and mission constraints. The dissertation also details new research in powered gravity assists. A review of literature on optimal powered gravity assists is presented, where many optimal solutions found are infeasible for realistic spacecraft missions. The need was identified for a mission feasible optimal powered gravity assist algorithm using only a single impulsive maneuver. The solution space was analyzed and a complete characterization was developed for solution types of the optimal single-impulse powered gravity assist. Using newfound solution space characteristics, an efficient and reliable optimal single-impulse powered gravity assist BVP algorithm was formulated. The mission constraints were strictly enforced, such as maintaining the closest approach above a minimum radius and below a maximum radius. An extension of the optimal powered gravity assist research is the development of a gravity assist BVP algorithm that utilizes an asymptote ΔV correction maneuver to produce ballistic gravity assist trajectory solutions. The efficient algorithm is tested with real interplanetary mission trajectory parameters and successfully converges upon ballistic gravity assists with improved performance compared to traditional methods. A hybrid approach is also presented, using the asymptote maneuver algorithm together with traditional gravity assist constraints to reach ballistic trajectory solutions more reliably, while improving computational performance.

Made available in DSpace on 2014-06-12T15:56:13Z (GMT). No. of bitstreams: 2 arquivo2770_1.pdf: 3435334 bytes, checksum: c4ebc011cd6476e268421539acd59c8c (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Associação para Promoção da Excelência do Software Brasileiro / O gerenciamento e o projeto de sistemas de engenharia complexos é um desafio interessante. A engenharia de sistemas é um campo interdisciplinar da engenharia focado na melhoria da qualidade de projetos de sistemas. Ela encoraja o uso de métodos e ferramentas como simulação, otimização, análise de confiabilidade e análise estatística para aumentar o conhecimento do sistema, frequentemente representado como um conjunto de modelos. Uma enorme variedade de sistemas dinâmicos precisa ser controlada e pode ser modelada usando os princípios da Teoria de Controle, a base da disciplina de engenharia de controle. Em particular, a engenharia de controle objetiva criar leis de controle para o sistema, que são modeladas usando diagramas de bloco (também chamados de diagramas de leis de controle) e validadas/verificadas usando simulação. Entretanto, a maior parte das validações de leis de controle realizadas na indústria é feita usando ferramentas de simulação como o Simulink, e simulações não cobrem todos os comportamentos do modelo. Além disso, não é fácil modelar uma arquitetura complexa na qual redundância e monitoramento são comumente usados para se obter segurança. Neste trabalho, nós apresentamos três principais contribuições: (1) um conjunto de regras de tradução de modelos Simulink para a algebra de processos CSP (Communicating Sequential Processes), incluindo uma infraestrutura para suportar vários blocos discretos de Simulink; (2) uma estratégia para validar a integração de uma proposta de arquitetura com as leis de controle; e (3) a validação de um sistema de controle de voo dos profundores de um avião produzido pela Embraer. Os resultados mostram que a estratégia pode ser aplicada a modelos complexos através do uso das técnicas formais de abstração de dados e verificação de modelos. Ademais, a estratégia proposta aprimora o processo de desenvolvimento padrão (modelo V) seguido pela indústria por encontrar potenciais defeitos em fases de especificação do projeto, reduzindo tempo de desenvolvimento e custos

Spacecraft trajectory optimization is a near-infinite problem space with a wide variety of models and optimizers. As trajectory complexity increases, so too must the capabilities of modern optimizers. Common objective cost functions for these optimizers include the propellant utilized by the spacecraft and the time the spacecraft spends in flight. One effective method of minimizing these costs is the utilization of one or multiple gravity assists. Due to the phenomenon known as the Oberth effect, fuel burned at a high velocity results in a larger change in orbital energy than fuel burned at a low velocity. Since a spacecraft is flying fastest at the periapsis of its orbit, application of impulsive thrust at this closest approach is demonstrably capable of generating a greater change in orbital energy than at any other location in a trajectory. Harnessing this extra energy in order to lower relevant cost functions requires the modeling of these “powered flybys” or “powered gravity assists” (PGAs) within an interplanetary trajectory optimizer. This paper will discuss the use and modification of the Spacecraft Trajectory Optimization Suite, an optimizer built on evolutionary algorithms and the island model paradigm from the Parallel Global Multi-Objective Optimizer (PaGMO). This variant of STOpS enhances the STOpS library of tools with the capability of modeling and optimizing single and multiple powered gravity assist trajectories. Due to its functionality as a tool to optimize powered flybys, this variant of STOpS is named the Spacecraft Trajectory Optimization Suite - Flybys with Impulsive Thrust Engines (STOpS-FLITE). In three test scenarios, the PGA algorithm was able to converge to comparable or superior solutions to the unpowered gravity assist (uPGA) modeling used in previous STOpS versions, while providing extra options of trades between time of flight and propellant burned. Further, the PGA algorithm was able to find trajectories utilizing a PGA where uPGA trajectories were impossible due to limitations on time of flight and flyby altitude. Finally, STOpS-FLITE was able to converge to a uPGA trajectory when it was the most optimal solution, suggesting the algorithm does include and properly considers the uPGA case within its search space.

Multiple gravity assist (MGA) spacecraft trajectories can be difficult to find, an intractable problem to solve completely. However, these trajectories have enormous benefits for missions to challenging destinations such as outer planets and primitive bodies. Techniques are presented to aid in solving this problem with a global search tool and additional investigation into one particular proximity operations option is discussed. Explore is a global grid-search MGA trajectory pathsolving tool. An efficient sequential tree search eliminates v∞ discontinuities and prunes trajectories. Performance indices may be applied to further prune the search, with multiple objectives handled by allowing these indices to change between trajectory segments and by pruning with a Pareto-optimality ranking. The MGA search is extended to include deep space maneuvers (DSM), v∞ leveraging transfers (VILT) and low-thrust (LT) transfers. In addition, rendezvous or nπ sequences can patch the transfers together, enabling automatic augmentation of the MGA sequence. Details of VILT segments and nπ sequences are presented: A boundaryvalue problem (BVP) VILT formulation using a one-dimensional root-solve enables inclusion of an efficient class of maneuvers with runtime comparable to solving ballistic transfers. Importantly, the BVP VILT also allows the calculation of velocity-aligned apsidal maneuvers (VAM), including inter-body transfers and orbit insertion maneuvers. A method for automated inclusion of nπ transfers such as resonant returns and back-flip trajectories is introduced: a BVP is posed on the v∞ sphere and solved with one or more nπ transfers – which may additionally fulfill specified science objectives. The nπ sequence BVP is implemented within the broader search, combining nπ and other transfers in the same trajectory. To aid proximity operations around small bodies, analytical methods are used to investigate stability regions in the presence of significant solar radiation pressure (SRP) and body oblateness perturbations. The interactions of these perturbations allow for heliotropic orbits, a stable family of low-altitude orbits investigated in detail. A novel constrained double-averaging technique analytically determines inclined heliotropic orbits. This type of knowledge is uniquely valuable for small body missions where SRP and irregular body shape are very important and where target selection is often a part of the mission design.