Quasi-satellite orbits (QSOs) are orbits around the smaller primary in three-body systems. The MMX mission (developed by JAXA, to be launched in 2024) will use QSOs to orbit Phobos, before landing on its surface. This work studies the feasibility of using the invariant manifolds of three-dimensional QSOs for designing landing trajectories, using the Mars-Phobos system as a case study. Applying continuation and bifurcation-analysis techniques, different families of QSOs were computed and their invariant manifolds propagated. Using a set of favorable manifolds as a reference, multiple maneuvers were designed via multiple-shooting and optimization techniques, producing feasible landing trajectories. The robustness of these trajectories was analyzed using a stability index and Monte Carlo simulations. It was found that using the invariant manifolds of QSOs to land is only possible for some families of QSOs. However, for these, the manifolds allow generating robust and propellant-efficient landing trajectories that are able to reach most of Phobos' surface.

Waveriders are high-lifting hypersonic configurations with great potential to become a future reusable launch vehicle concept. However, in a re-entry flight scenario, standard waverider designs face challenges such as stability, controllability, heat load management, and performance at off-design conditions. In this research, a baseline waverider design is established and then modified to feature blunt leading edges, aerodynamic surfaces for trim and control, and fins for lateral-directional stability. Shape variations are then introduced using central-composite designs, and the re-entry trajectories of all generated vehicles are optimised numerically in a constrained multi-objective framework. Performance indices (cross-range, heat load, pitch stability, lateral-directional stability and aileron controllability) are computed for each optimal trajectory, and response surfaces relating them with the shape variables are constructed and optimised independently using an interior point method. From this process, desirable, irrelevant and conflicting shape features for the various performance indices are identified. A novel local surface inclination method blending the tangent-wedge and modified Newtonian models was introduced to compute the aerodynamic force and moment coefficients of the waveriders. Finally, an existing program to compute the convective heat flux on the surface of blunt-nosed vehicles at hypersonic speeds was computationally optimised, and then extended to support waverider-like geometries with leading edges and stagnation lines.

While the space industry expands rapidly and space exploration becomes ever more relevant, this thesis aims to automate the design of Multiple Gravity-Assist (MGA) transfers using low-thrust propulsion. In particular, during the preliminary design phase of space missions, the combinatorial complexity of MGA sequencing is large and current optimisation approaches require extensive experience and can take days to simulate. Therefore, a novel optimisation approach is developed -- called the Recursive Target Body Approach -- that uses the hodographic-shaping low-thrust trajectory representation together with a combination of tree-search methods to automate the optimisation of MGA sequences. The approach gradually constructs the expected optimal MGA sequence by recursively evaluating the optimality of subsequent gravity-assist targets. Moreover, the approach includes novel figures of merit as well as parallelisation concepts to increase the robustness and accelerate the convergence. An Earth-Jupiter transfer with a maximum of three gravity assists is considered as a reference problem. Extensive tuning improved the quality of the MGA trajectory representations substantially and as a result, a robust low-thrust trajectory optimisation could be ensured. A distinct group of highly fit MGA sequences is consistently found that can be passed to a higher-fidelity method. In conclusion, the Recursive Target Body Approach can automatically and reliably be used for the preliminary optimisation of low-thrust MGA trajectories.

The number of space objects has largely increased in the recent years, becoming a considerable threat to the present and future of satellite operations and human spaceflight. This introduces a need to accurately compute the risk of collision between satellites and space debris. Current methodologies are limited by the type of encounter and the vehicle shape, usually simplified by a sphere. These assumptions rely mainly on linearization of the dynamics and simplification of the uncertainty distribution as a Gaussian function. Developing a collision probability calculation method that overcomes these limitations and provides high-accuracy results is the topic of this work. The methodology developed follows a hybrid combination of trajectory propagation and statistical methods for uncertainty propagation. With the propagation method covariance information of the satellite position and velocity will be available. Finally, the method is adapted to any satellite geometry by developing a numerical quadrature technique based on a combination of spheres to model the real body shape. The combination of these methodologies to compute the collision probability has been verified with a set of test cases by means of a Monte Carlo simulation and compared to alternative algorithms. It is found that the method improves the accuracy in calculating the collision probability by more than 70% with respect to conventional alternatives. Regarding real-life scenarios, the Cosmos-2251/Iridium-33 and the Chang Zheng-4C/Cosmos-2004 encounters are simulated. In both cases, the time of encounter and collision risk have been correctly estimated with the developed method. Finally, in view of the recent destruction of satellite Cosmos-1408 as a result of an anti-satellite missile test, a screening of its resulting debris threatening the International Space Station (ISS) is performed. During a two-week period, ten close encounters were detected, one of which posed a significant risk to the ISS. When applying the method considering the real shape of the ISS, the collision probability decreases by two orders of magnitude, proving the significance of this approach to correctly estimate the risk and guide space operations.

IAC will be developing a new Transportable Optical Ground Station (TOGS). It is a telescope that is intended to be used for quantum key distribution in a number of events. Using AO for free-space propagation stabilises the optical signal on a detector significantly, and maximises the received signal by returning near-diffraction limited performance to the optical system and stabilising the channel transmission and noise. The goal of this thesis will be to design a controller for an AO system that will be used for the new Transportable Optical Ground Station (TOGS) of IAC.

Autonomously landing a spacecraft on the surface of a planetary body with a degree of precision in the order of meters is highly challenging. Over the course of time, the landing ellipse, defined as the region with a 99% likelihood of where a space vehicle will land, has improved steadily but currently still has dimensions in the order of kilometers. The first and single Martian spacecraft that has performed a guided atmospheric entry and utilized precision landing technologies is the Mars Science Laboratory (MSL). The MSL probe and its focal point, the Curiosity rover, has thus been the most advanced mission yet to have flown to Mars. Nonetheless, space missions to the Red Planet have thus-far never landed following fuel optimal paths. Similarly, dispersions for landing on Titan with current technologies expand to hundreds of kilometers. The only reference mission to Titan is the Huygens probe, which has not utilized precision landing technologies nor optimal path planning. Besides, the goal of the Cassini-Huygens mission was to maximize descent time to augment scientific data retrieval of Titan's atmosphere. As part of the NASA Space Exploration Technology Directorate, a parafoil is proposed for landing on Titan due to its cost effectiveness, ease of deployment, relatively low mass compared to the prospective payload and capabilities of precise autonomous delivery. While considering all phases of Entry, Descent and Landing (EDL) and all elements of Guidance, Navigation and Control (GNC), the central focus of the research was put on the (powered and parafoil) terminal descent phase. The research core concerns a convex optimization programming approach to guarantee soft-landing. The algorithm has been verified based on the extensive Mars powered descent guidance literature. As part of the research conducted at NASA/JPL/Caltech, the algorithm has been extended to become compatible with landing a parafoil on Saturn's moon Titan. Throughout the discussion a distinction is made between lossless and successive convexification for optimal guidance. Both types have been simulated to either compute fuel optimal paths for powered Mars landing or pull-power optimal paths for parafoil Titan landing. The soft-landing is guaranteed while adhering to imposed mission constraints. By using the full capability of the spacecraft unprecedented precision may be achieved. This will enable engineers and scientists to reach the most alluring places on planetary bodies, thereby providing humanity a deeper understanding of the Universe.

Flapping wing micro air vehicles (FWMAV's) are a subcategory of unmanned aerial vehicle which use flapping wings for thrust generation. The high agility and maneuverability of FWMAV's are very favorable attributes, making them more applicable in cluttered spaces. A tailless FWMAV called the Delfly Nimble has been developed at the Delft University of Technology. Due to the inherent instability of the tailless design an active controller is required to ensure safe and stable flight of the drone. In previous research, models have been developed for the longitudinal dynamics of the Delfly Nimble. In this paper, a grey-box state-space model of the lateral body dynamics in hover conditions is identified using system identification techniques. The parameters which needed to be estimated were stability and control derivatives, and they were obtained with a least-squares approach. Free-flight experiments were performed to generate the identification and validation data. A doublet train was used in the identification experiments, with the gains of the controller adjusted in such a way that maximum excitation was acquired. The identified model has been validated with various maneuvers. These included doublets, 112-maneuvers, maneuvers using coupled inputs, and maneuvers with sideways flight. The resulting model is able to predict the state derivatives of most maneuver accurately, reaching accuracies of over 90% for maneuvers close to hover. Moreover, in closed-loop configuration it is able to simulate the state response accurately, with accuracies of over 85% for maneuvers close to hover, and remains stable, making it applicable for controller design and stability analysis. Finally, based on the model the inherent instability of the lateral body dynamics was also confirmed, for there are eigenvalues with positive real parts.

Current-day space vehicle are equipped with a passive Thermal Protection System (TPS), but these systems operate at the edge of their capabilities. The research into the next generation reusable space vehicle demands the use of active TPS, these systems are not limited to the capabilities of the used material but depend on the active cooling mechanism. A system of cooled metallic TPS is developed at the TU Delft resulting in an increase in the maximum allowable thermal load for a given TPS temperature, this system is the enhanced radiation cooling TPS. The research question is: "Can an active thermal protection system improve the flying characteristics and the flight performance of a re-entry vehicle?". The first step in answering this question is to verify the process behind the active TPS. This thesis aims to design an experiment to verify this process. To answer the research question two tools were developed: a flight simulator and a thermodynamic analyser. The flight simulator provides insight in the behaviour of the rocket and shows the consequences of implementing the enhanced radiation cooling TPS on the rocket. The thermodynamic analyser is used to estimate the wall temperature of the system and shows the effect of the sensitivity analysis of the design of the cooling subsystem. The enhanced radiation cooling system is designed to be mounted on the T-Minus Dart and an experiment to verify the impact of the active TPS is derived using the nominal mission of the rocket. Sensitivity analysis resulted in thin outer shell and a insulation sphere filled with the coolant. The outer shell needs to be as thin as possible in order to maximize the cooling effect. For an outer shell of 0.5 millimetres, the maximum allowable thermal load can be doubled in comparison with an non-cooled flight. If an identical thermal loading is assumed for two return vehicles, the active cooled vehicle can be designed with a nose radius of around 30 % smaller that the non-cooled vehicle. This will result in a vehicle with a higher lift-over-drag ratio, extending the return trajectory which increases the safety of the re-entry flight. The validity of performing an enhanced radiation cooling experiment is shown by the use of the tools developed in this thesis. The incoming heat flux can be doubled while maintaining the same wall temperatures if the cooling system is applied. This opens the possibility of redesigning re-entry vehicles to achieve a high lift-to-drag ratio.

The amount of propellant required to perform deep-space maneuvers usually consists of a large percentage of the total spacecraft mass. In the early '90s, a new technique was experimented at the end of the Magellan mission, which employed the atmosphere of Mars itself, to reduce the eccentricity of the orbit over a long period of time. Said action was named aerobraking and the design of the required onboard software to perform this maneuver, is the main topic of this thesis. The navigation part of the software has the purpose of determining the current spacecraft state (position, velocity and attitude). Two navigation systems have been implemented in this research and they differ in the fact that one is purely based on data available onboard (such as accelerometer measurements and a simplified environment model), whereas the other uses observations from an unspecified positioning system, to complement the onboard model. The tasks of the guidance system can be summarized as: estimating the minimum and maximum values of the pericenter altitude and targeting the midpoint of said range. The first function is achieved by considering the thermodynamic limitations of the spacecraft and the restrictions on aerobraking duration, whereas to attain the second purpose, use is made of a maneuver estimator. Both an attitude and an orbit controller are designed for the mission. A proportional, integral and derivative controller is used to regulate the rotational motion of the spacecraft, whereas, orbit control is realized by assuming impulsive shots at apoapsis. Based on the analyses performed, it was concluded that this GNC system partly fulfills its duties. In fact, it is able to 1) reduce the mass of an interplanetary spacecraft, by requiring the employment of 82 instead of more than 1000 m/s of velocity increments, and 2) to maintain a low navigation error (for most of the orbit the position error is within 50 m), but, on the other hand, it is not capable of providing a robust performance. In particular, the excessive heating experienced during the atmospheric phases of the mission, poses a large threat to the thermal and overall integrity of the spacecraft, possibly jeopardizing the whole mission.

Though NanoSats are becoming increasingly capable of featuring active payloads, and acquiring inertial data at arcsec level precision; the payload operational duty-cycle largely remains limited by its data downlink capabilities. NanoSat laser communication terminal (LCT) promises 1 Gbps data downlink capabilities. However, LEO to ground free space optical data transmission requires precision attitude knowledge under agile ground target tracking conditions. Under such stringent operational conditions, the calibration of gyro-stellar misalignment and scale factors is a well-established practice for traditional satellites. Nevertheless, the impact of such non-idealities in the context of MEMS gyro-stellar based NanoSat precision pose estimation is unclear. Furthermore, the gyro-stellar calibration performance that can be achieved with NanoSat ADCS system requires further investigation. Under agile operational conditions, slew rate induced star tracker drop-out is common for NanoSats, which limits the operational envelope of agile precision tracking missions. To increase our understanding of attitude knowledge estimation capability of today's NanoSats, this thesis work is extended at Hyperion Technologies. In collaboration with Hyperion Technologies, gyro-stellar sensors are characterised; and CubeCAT LCT is used to laydown the reference payload and mission requirements of an agile precision terrestrial target tracking NanoSat mission. Based on state steady noise PSD properties, and attitude knowledge requirements set by the LCT, gyro-stellar configurations are selected, and characterised. A rigid body attitude simulator is developed, considering the characterised sensor suite, to generate representative nominal and non-ideal sensor outputs under four different mission phases: 1.) Inertial pointing with no angular rate, 2.) Non-harmonic sinusoidal manoeuvres 3.) Agile precision ground target tracking and 4.) Inertial target tracking with non-zero angular rate. Reaction-wheel time delay and torque limits are evaluated to analyse the feasibility of attitude pointing requirements under agile target tracking conditions. Due to favourable properties of robustness to large initialisation errors, fast convergence, and preservation of attitude quaternion unity norm constraint; UnScented QUaternion Estimator (USQUE) variant of UKF based filter is synthesised for attitude estimation. The USQUE filter is further extended to facilitate the calibration of gyro-stellar misalignment and scale factors. It is demonstrated that the presence of gyro-stellar misalignment and scale factor, and star tracker occultation under agile slew rates significantly deteriorates the attitude estimation performance of USQUE based attitude estimator. Star tracker misalignments and dropouts are observed to have a significantly larger impact on the attitude knowledge estimation performance, when compared against MEMS rate-gyro scale factor and misalignment. Degraded MEMS rate gyro sensors are observed to have little impact on the attitude knowledge estimation performance of 6/7 state USQUE filter. However, it has a considerable impact on the convergence performance of star tracker misalignment calibration. More persistent calibration manoeuvres are observed to improve the star tracker misalignment parameter estimation performance. Gyro misalignment and scale factor calibration objectives were not met. A root-cause analysis showed that the signal distortions introduced by such non-idealities are below the gyro-stellar noise floor. Calibration filter synthesised has the potential to improve autonomy, reduce commissioning and ground calibration times, and enhance NanoSat pose estimation performance.

With the onset of the age of space travel, asteroid missions have been steadily gaining interest. The pristine nature of asteroids due to their preserved state since the formation of the Solar System is an opportunity to unravel many mysteries about the Solar System. Also with the ever-growing need for resources, asteroids prove to be a plentiful source. With the discovery of asteroids in the close vicinity of our planet and a probable threat to the preservation of life, a need for defence missions has also arisen. The ever-growing need for better computational speed and accuracy has led to the development of new representations for attitude and position of the spacecraft in the past. The usual methods of representations of position and attitude (pose) are the Cartesian coordinates and quaternions. A recent development is the simultaneous representation of the pose of the spacecraft using dual quaternions which are eight-dimensional vectors. In this thesis, an attempt to incorporate these state-of-the-art guidance technologies to asteroid missions has been made. The novelty in this thesis is, using dual quaternions for SC pose and attitude representation to autonomously guide the spacecraft for mapping an asteroid and perform a touch and go descent using sampling-based motion predictive optimisation and successive convexification respectively. After the development and verification of these algorithms, different scenarios have been designed to find out the robustness of the dynamic successive convexification method. The scenarios have been run by both the Cartesian quaternion and dual quaternion based algorithms. They are found to behave similarly in their results, besides the latter being computationally more expensive as proved by different theses so far. The algorithm performs better than the one developed by Szmuk et al. (2017), but faces difficulties with badly scaled problems as is the nature of missions to asteroids. The software used for the thesis is ECOS, which faces numerical problems in these mission scenarios even when the problem is feasible and has an optimal result. The availability of a solution to the optimal control problem depends on the scaling of the penalty weights used in the cost function to penalise virtual controls and trust region, which are used to prevent infeasibility and bound the problem, respectively. It also depends on finding an appropriate final time for the descent along with the number of nodes for discretisation. This research proves, that successive convexification indeed provides a speedy solution for an autonomous precision descent but needs further work to make it robust and stable. The outcome of this thesis is to carry out further research to understand the complex relations, between the scale of the problem, simulation parameters for the optimal control problem and final time to make the algorithm robust and safe for an autonomous mission. Another important future research prospect is to incorporate the sampling based model predictive optimisation, for the SC to autonomously map the target body and help in selecting a landmark for a descent.

The next step in spaceflight, among others, is the development of a reusable launch vehicle (RLV) suitable for manned missions. All existing designs of re-entry vehicles are either ballistic or low L/D vehicles. In the future, the aim is to develop a high L/D vehicle, because such vehicles experience lower g-loads, making the flight comfortable for manned flights. The development of these vehicles can be useful for both, space (for example, space tourism) and military applications (for example, long-range missiles). Thermal protection system (TPS) is deemed critical to the RLV development, as high L/D vehicles are expected to experience higher thermal loads. Existing TPS solutions are not suitable for this purpose. Therefore, arises the need to find reusable TPS solutions that can sustain the desired thermal loads. Flight testing is a crucial step for developing any hypersonic system, this applies to the TPS design as well. This study aims to investigate the influence of TPS on designing the mission and vehicle for a test flight. From the various developed and proposed TPS designs in literature, a TPS solution is selected, to meet the requirements identified for future RLVs. The solution is an active cooling concept (cooled metallic TPS), named Enhanced radiation cooling, that uses water as a coolant. Based on a preliminary design investigation, suitable materials are selected and the thickness of the layer is determined. The performance of the proposed TPS design, i.e., the thermal load-bearing ability, is assessed using a transient thermal analysis tool developed for this purpose. The outcome of this analysis proves that the proposed design does not meet the thermal load requirements identified in this study. Nonetheless, the concept shows substantial improvement in performance, it can sustain almost double the heat flux as compared to an uncooled system. To meet the heat flux requirements, a few modifications in the design are proposed and analysed. These modifications increase the complexity of the system and have other adverse consequences that must be addressed. However, thermal analysis proves that the heat flux requirements, identified at the start of this study, are satisfied. A sensitivity analysis of this modified cooling system shows that the performance of the design is not influenced by material uncertainties. Additionally, the design is found to be robust under varying mission and design parameters, within reasonable bounds. These results can serve as a preliminary input for designing a test vehicle and mission.

During its lifetime a space launcher is subjected to extreme heat loads. To protect space vehicles from these heat loads and their resulting temperatures they are equipped with a Thermal Protection System (TPS). Heat loads are typically the largest during flight through the atmosphere. The research question addressed in the thesis is: how robust is a thermal protection system design for a spaceplane wing-body configuration to variations with respect to the design parameters or trajectory taking into account heat transfer through radiation and conduction in three dimensions? To answer the research question a tool was developed which is capable of designing a TPS and optimizing the insulation layer thickness. Furthermore, a trajectory simulation was made for the reentry phase. From the trajectory specifics the heat flux over the vehicle over time could be generated, which is the source of the temperature increase. In the TPS design tool the first major task is to divide the vehicle into different TPS areas, based on the temperatures that are experienced at each of these areas of the skin surface. A thermal analysis is performed, taking into account both conduction in three dimensions and radiation to outer space as well as to the inner subsystems of the vehicle. From this analysis the maximum experienced temperature can be deduced for each area. When the TPS design is found, it is aimed to optimize the insulation layer thicknesses in all TPS areas. The goal is to find a design that is as light as possible, thus with a minimum insulation layer thickness, while not exceeding the maximum temperatures of the TPS types and underlying structure. A sensitivity study was performed to investigate the robustness of the TPS design resulting from the tool. The performance of the TPS design was tested when small changes were made to it, for the nominal reentry trajectory of the reference vehicle. Furthermore the TPS designs performance was analyzed for small changes in the trajectory. From the analysis of the results of the developed tool it was found that a TPS design can be developed for a simple wing-body configuration, under the specified conditions. However, the functionality of the TPS design is limited. Improvements must be made to the developed tool to increase its performance, so that it can come to an acceptable TPS design. It is suspected that with suggested improvements the tool will work properly, and a well functioning TPS design can be made. However, further research is required to ensure this.

Uranus is one of the most intriguing and unexplored bodies of the Solar System. Its mysteries include its active atmospheric dynamics, its low internal energy, its extreme obliquity, its complex magnetic field, and its ring and satellite system containing possible ocean worlds. As of today, none of the current formation and evolution models can explain all its chemical and dynamical aspects. An in-situ mission to study Uranus' atmosphere could provide answers to this planet's mysteries, enabling the measurement of its deeper layers. A 6 DoF flight simulator was designed, with a focus on identifying the specifications and limitations of its Guidance, Navigation, and Control modules, for feasibly flying in Uranus' challenging atmosphere, and providing new science return. The mission architecture consists of two gliders flying near the planet’s equator and north pole until the 100 bar pressure level for around 13 Earth days, supported by an orbiting spacecraft in a circular, equatorial, and synchronous orbit, for continuous trajectory tracking and relay of the scientific data to Earth ground stations. Due to Uranus’ opaque atmosphere, typical optical navigation sensors such as star sensors, Sun sensors, and imagers are avoided. Instead, the modelled navigation sensors are taken from the payload suite.

In the context of metaheuristic global optimization, we present the definition and development of two new ant colony optimizers (ACO): a single-objective mixed-integer one, called ACOmi, and a multi-objective hypervolume-based one, called MHACO. In particular, after having performed a verification and validation phase over a wide set of problems (including various space missions such as Cassini, Messenger, Rosetta, and others), we focus on their application to a solar polar sailing mission to the Sun, attempting to minimize its mission cost and duration. Therefore, building on previous studies of such a mission scenario, we first constructed a model for simulating the journey of the sail from a geocentric GTO to the Sun, not only accounting for gravitational forces, but also atmospheric forces, the non-ideal solar radiation pressure force, and other environmental aspects. Then, a guidance model for the sail was set up, so that the attitude of the sail could be controlled during its journey to the Sun. This entire framework was formulated as both a single and multi-objective problem. Finally, a trade-off was performed between the newly developed ACO and other state-of-art global optimizers. For the single-objective case, these include artificial bee colony, simple genetic algorithm, self-adaptive differential evolution, particle swarm optimization, and other methods. While for the multi-objective scenario three different optimizers have been tested against the multi-objective ant colony extension: an evolutionary algorithm with decomposition, a nondominated sorting genetic algorithm and a multi-objective variant of particle swarm optimization. The found results are very promising: for the single-objective problem, the ant colony optimizer has managed to outperform all the algorithms. Whilst for the multi-objective case, the genetic algorithm seems to provide the best Pareto fronts, although the results are very competitive with those of the ACO, especially for lower function evaluations. In the end, besides providing the scientific community with new powerful global optimizers for SO and MO problems, we managed to halve the mass of the solar sail compared to previous studies, while still keeping a similar time of flight.

During the last decades, large deployable structures are starting to be seen as a plausible configuration to multiple space missions, such as solar sailing, LEO (Low Earth Orbit) deorbiting missions or solar power generation. Technological advances in key areas, such as thin film solar cells or new deployment methods, as well as the miniaturization of satellites and their components, have considerably increased the usefulness of this design. The research presented in this document aims to contribute to these technological developments, helping to unfold the whole potential of this structural solution. This research comprises the MSc thesis of the author, in partial fulfillment of the MSc in Aerospace Engineering by the Technical University of Delft. The research was conducted during an internship at the department of Guidance Navigation and Control (GNC) Systems, Institute of Space Systems, German Aerospace Center (DLR). The research focuses in the study of the behavior of large thin flexible structures (LTFSs) in space from the perspective of the attitude determination and control system (ADCS). This work was performed in close relation to the DLR’s mission GoSolAR (Gossamer Solar Array). The contributions of the research can be classified in two areas, related to the modeling of the structure and to the design of the ADCS. In relation to the first one, a methodology to integrate the flexibility of a structure into its equations of motion is explained from a theoretical perspective and implemented over a flexible spacecraft. This methodology is based in Lagrange’s equations and can be applied to diverse structures, allowing modeling accurately the dynamics of the system while maintaining the model comprehensive and of relatively low order. The implementation of this approach leads to equations of motion containing both rigid and flexible motion, enabling to conduct an evaluation of the impact of the flexibility of a structure on its dynamics in a space environment. The second major area in which this thesis aims to contribute to the body of knowledge is related to the design and evaluation of attitude controllers targeting flexible satellites. Different controller’s designs are proposed, based in: 1) a linear-quadratic regulator (LQR) approach, 2) robust control theory, particularly in the minimization of HInf and H2 norms, and 3) a control approach based in analytical dynamics, known as the Udwadia–Kalaba approach. The performance of these designs was evaluated not only in relation to control instructions related to the rigid motion of the satellite, e.g. angular rate, but also to the capability of each controller of damping the system, reducing the vibrations that appear due to its flexibility. The particularities that need to be considered when implementing each controller are also studied, in order to give a clear idea of when would each controller be an adequate control solution. The result is a set of different control designs, including for each of these designs: 1) the methodology to derive the controller, 2) the performance of the controller and 3) the particularities and limitations of its implementation.

This paper investigates the performance of an autonomous navigation system to navigate a spacecraft in the proximity of a binary asteroid system using optical and laser ranging measurements. The knowledge about the binary asteroid is limited to its orbital parameters and ellipsoid shape models. The accelerometer bias random walk is included in the estimation process. Over a four-hour landing maneuver starting from 6770 m altitude and ending at 550 m, the mean position estimation uncertainty is 41.6 m (3σ). It is shown that the navigation accuracy is sensitive to the Sun phase angle, the irregularity of the asteroid shape, and the goodness of fit of the ellipsoid shape model. The paper demonstrates that the navigation system is robust to large errors in the initialization of the extended Kalman filter state. The impact of image distortion and two types of image noise on the navigation performance are investigated.

An analysis of attitude controller concepts, including four attitude flight controllers, for the re-entry of the HORUS-2b. The four concerning attitude flight controller concepts are the benchmark Linear Quadratic Regulator (LQR), Model predictive Controller, Incremental Non-linear Dynamic Inversion (INDI) and Sliding Mode Controller. Each attitude flight controller was employed in a full Guidance, Navigation and Control system and subsequently applied to a winged re-entry vehicle, the HORUS-2b. It was found that the INDI-controller is the most suitable attitude controller technique for real world entry GNC-systems. The INDI controller showed excellent performance with respect to disturbance rejection, amplification, robustness and implementation effort. Besides the INDI controller, the benchmark LQR-controller achieves excellent performance. In the current GNC-simulation set-up the LQR-controller is the best able to perform a re-entry, having zero control failures and an equal robustness to the INDI controller. Disadvantages of the LQR-controller are the large amplification of an oscillating signal and the implementation effort.

In recent years Adaptive Critic Designs (ACDs) have been applied to adaptive flight control of uncertain, nonlinear systems. However, these algorithms often rely on representative models as they require an offline training stage. Therefore, they have limited applicability to a system for which no accurate system model is available, nor readily identifiable. Inspired by recent work on Incremental Dual Heuristic Programming (IDHP), this paper derives and analyzes a Reinforcement Learning (RL) based framework for adaptive flight control of a CS-25 class fixed-wing aircraft. The proposed framework utilizes Artificial Neural Networks (ANNs) and includes an additional network structure to improve learning stability. The designed learning controller is implemented to control a high-fidelity, six-degree-of-freedom simulation of the Cessna 550 Citation II PH-LAB research aircraft. It is demonstrated that the proposed framework is able to learn a near-optimal control policy online without a priori knowledge of the system dynamics nor an offline training phase. Furthermore, it is able to generalize and operate the aircraft in not previously encountered flight regimes as well as identify and adapt to unforeseen changes to the aircraft’s dynamics.

This study demonstrates an effective systematic control design procedure by applying H∞ Loop-Shaping with a structured controller on an agile aerospace vehicle with a focus on automation. The gain-scheduled implementation is additionally described and tested with non-linear simulations, including a realistic moving point-hit scenario with guidance. The imposed robustness and performance requirements are met for most linear design points and for the non-linear simulations. The resulting autopilot design procedure is deemed effective in both the design procedure and implementation. It is subject to certain recommendations for improvement and extension.