This thesis proposes a method of performing fault detection and isolation in spacecraft attitude determination and control systems. The proposed method works by deploying a trained neural network to analyze a set of residuals that are dened such that they encompass the attitude control, guidance, and attitude determination subsystems. Eight neural networks were trained using either the resilient backpropagation, Levenberg-Marquardt, or Levenberg-Marquardt with Bayesian regularization training algorithms. The results of each of the neural networks were analyzed to determine the accuracy of the networks with respect to isolating the faulty component or faulty subsystem within the ADCS. The performance of the proposed neural network-based fault detection and isolation method was compared and contrasted with other ADCS FDI methods. The results obtained via simulation showed that the best neural networks employing this method successfully detected the presence of a fault 79% of the time. The faulty subsystem was successfully isolated 75% of the time and the faulty components within the faulty subsystem were isolated 37% of the time.

As spacecraft today become increasingly smaller, the demand for smaller components and sensors rises as well. The smartphone, a cutting edge consumer technology, has impressive collections of both sensors and processing capabilities and may have the potential to fill this demand in the spacecraft market. If the technologies of a smartphone can be used in space, the cost of building miniature satellites would drop significantly and give a boost to the aerospace and scientific communities.Concentrating on the problem of spacecraft orientation, this study sets ground to determine the capabilities of a smartphone camera when acting as a star camera. Orientations determined from star images taken from a smartphone camera are compared to those of higher quality cameras in order to determine the associated accuracies. The results of the study reveal the abilities of low-cost off-the-shelf imagers in space and give a starting point for future research in the field.The study began with a complete geometric calibration of each analyzed imager such that all comparisons start from the same base. After the cameras were calibrated, image processing techniques were introduced to correct for atmospheric, lens, and image sensor effects. Orientations for each test image are calculated through methods of identifying the stars exposed on each image. Analyses of these orientations allow the overall errors of each camera to be defined and provide insight into the abilities of low-cost imagers.

Spin-stabilized spacecraft generally rely on sun and three-axis magnetic field sensor measurements for attitude determination. This study experimentally determines the total accuracy of attitude determination solutions using modest quality sensors. This was ac- complished by having a test spacecraft collect data during spinning motions. The data was then post-processed to find the attitude estimates, which were then compared to the exper- imentally measured attitude. This same approach will be used to test the accuracy of the attitude determination system of the DICE spacecraft to be built by SDL/USU.

Presented here are electron-induced electron yield measurements from high-resistivity, high-yield materials to support a model for the yield of uncharged insulators. These measurements are made using a low-fluence, pulsed electron beam and charge neutralization to minimize charge accumulation. They show charging induced changes in the total yield, as much as 75%, even for incident electron fluences of <3 fC/mm2, when compared to an uncharged yield. The evolution of the yield as charge accumulates in the material is described in terms of electron recapture, based on the extended Chung and Everhart model of the electron emission spectrum and the dual dynamic layer model for internal charge distribution. This model is used to explain charge-induced total yield modification measured in high-yield ceramics, and to provide a method for determining electron yield of uncharged, highly insulating, high-yield materials. A sequence of materials with progressively greater charge susceptibility is presented. This series starts with low-yield Kapton derivative called CP1, then considers a moderate-yield material, Kapton HN, and ends with a high-yield ceramic, polycrystalline aluminum oxide. Applicability of conductivity (both radiation induced conductivity (RIC) and dark current conductivity) to the yield is addressed. Relevance of these results to spacecraft charging is also discussed.

With the rapid growth of space activities and advancement of aerospace science and technology, many autonomous space missions have been proliferating in recent decades. Control of spacecraft in proximity operations is of great importance to accomplish these missions. The research in this dissertation aims to provide a precise, efficient, optimal, and robust controller to ensure successful spacecraft proximity operations. This is a challenging control task since the problem involves highly nonlinear dynamics including translational motion, rotational motion, and flexible structure deformation and vibration. In addition, uncertainties in the system modeling parameters and disturbances make the precise control more difficult. Four control design approaches are integrated to solve this challenging problem. The first approach is to consider the spacecraft rigid body translational and rotational dynamics together with the flexible motion in one unified optimal control framework so that the overall system performance and constraints can be addressed in one optimization process. The second approach is to formulate the robust control objectives into the optimal control cost function and prove the equivalency between the robust stabilization problem and the transformed optimal control problem. The third approach is to employ the è-D technique, a novel optimal control method that is based on a perturbation solution to the Hamilton-Jacobi-Bellman equation, to solve the nonlinear optimal control problem obtained from the indirect robust control formulation. The resultant optimal control law can be obtained in closedorm, and thus facilitates the onboard implementation. The integration of these three approaches is called the integrated indirect robust control scheme. The fourth approach is to use the inverse optimal adaptive control method combined with the indirect robust control scheme to alleviate the conservativeness of the indirect robust control scheme by using online parameter estimation such that adaptive, robust, and optimal properties can all be achieved. To show the effectiveness of the proposed control approaches, six degree-offreedom spacecraft proximity operation simulation is conducted and demonstrates satisfying performance under various uncertainties and disturbances.

This thesis introduces the analysis of a novel device which, capitalizing on recent advances in gossamer solar sail technology, offers the possibility of propellantless satellite deorbiting and attitude control. By taking advantage of aerodynamic drag effects, a lightweight sail can rapidly deorbit a satellite. At the same time, the sail provides an ideal substrate for a large area magnetic torque coil for attitude control. Through the use of orbit propagation software, the performance of an implementation of this "MagSail" on a Low Earth Orbit (LEO) small satellite is simulated. The analysis is set forth in three parts. First the orbit decay profile of the satellite under the effects of atmospheric drag is presented. The results are interpreted for various initial orbits. Next, the actual torque generation of the MagSail is analyzed. Emphasis is placed on how various design parameters change the magnetic moment of the sail. Finally, a six degree of freedom simulation, combining both orbit propagation and PD attitude control demonstrates a possible implementation of the sail's attitude control capabilities. The work presented in this thesis provides an in-depth look at the deorbiting performance of large-area, low-mass LEO satellites. This research provides a theoretical framework for the development of compact, cost-effective propellantless propulsion and space debris mitigation systems.

In trajectory optimization, a common objective is to minimize propellant mass via multiple gravity assist maneuvers (MGAs). Some computer programs have been developed to analyze MGA trajectories. One of these programs, Parallel Global Multiobjective Optimization (PaGMO), uses an interesting technique known as the Island Model Paradigm. This work provides the community with a MATLAB optimizer, STOpS, that utilizes this same Island Model Paradigm with five different optimization algorithms. STOpS allows optimization of a weighted combination of many parameters. This work contains a study on optimization algorithm performance and how each algorithm is affected by its available settings. STOpS successfully found optimal trajectories for the Mariner 10 mission and the Voyager 2 mission that were similar to the actual missions flown. STOpS did not necessarily find better trajectories than those actually flown, but instead demonstrated the capability to quickly and successfully analyze/plan trajectories. The analysis for each of these missions took 2-3 days each. The final program is a robust tool that has taken existing techniques and applied them to the specific problem of trajectory optimization, so it can repeatedly and reliably solve these types of problems.

Understanding the space environment and contamination concerns of a spacecraft is critical in designing a successful mission. The ability for a spacecraft to meet its science objectives relies on systems functioning as intended. A concern for maintain- ing performance while on orbit is molecular contamination. Silicones have previously been shown to form a silica layer on their surfaces when exposed to atomic oxygen. For silicone contamination, this translates to a silica film on the contaminated surface. Missions such as Long Duration Exposure Facility and Evaluation of Oxygen Interactions with Materials III have indicated that the silica film can trap deposits of carbon contamination to the surface during its formation. This phenomenon was explored in this research using RTV-S 691 silicone and Braycote 601EF for the carbon-based contaminant. The experiment involved contaminating an aluminum substrate in three different configurations; one for each contaminant individually on the substrate, and one with both contaminants. These samples were exposed to atomic oxygen for a period of 24 hours, then analyzed with Fourier transform infrared spectroscopy. The trends in infrared spectra for the different test cases were characterized for comparison. The trend for samples with a carbon-to-silicone contamination ratio of greater than ten to one showed peaks corresponding to those seen on the singularly contaminated samples. When the concentration of silicone was increased, the trend in spectral results showed peaks corresponding to Braycote before atomic oxygen exposure. At certain concentrations of RTV silicone to Braycote, the trends suggest Braycote is partially protected from atomic oxygen by a silica film. This indicates that silicone conversion to silica in atomic oxygen can trap contaminants to a surface.

The Cal Poly Spacecraft Dynamics Simulator, also known as the Pyramidal Reaction Wheel Platform (PRWP), is an air-bearing four reaction wheel spacecraft simulator designed to simulate the low-gravity, frictionless condition of the space environment and to test and validate spacecraft attitude control hardware and control laws through real-time motion tests. The PRWP system was modified to the new Mk.III configuration, which adopted the MATLAB xPC kernel for better real-time hardware control. Also the Litton LN-200 IMU was integrated onto the PRWP and replaced the previous attitude sensor. Through the comparison of various control laws through motion tests the Mk.III configuration was tested for robust control law verification capability. Two fixed-gain controllers, full-state feedback (FSFB) and linear quadratic regulator with set-point control(LQRSP), and two adaptive controllers, nonlinear direct model reference adaptive controller (NDMRAC) and the adaptive output feedback (AOF), were each tested in three different cases of varying plant parameters to test controller robustness through real-time motion tests. The first two test cases simulate PRWP inertia tensor variations. The third test case simulates uncertainty of the reaction wheel dynamic by slowing down the response time for one of the four reaction wheels. The Mk.III motion tests were also compared with numerical simulations as well as the older Mk.II motion tests to confirm controller validation capability. The Mk.III test results confirmed certain patterns from the numerical simulations and the Mk.II test results. The test case in which actuator dynamics uncertainty was simulated had the most effect on controller performance, as all four control laws experienced an increase in steady-state error. The Mk.III test results also confirmed that the NDMRAC outperformed the fixed-gain controllers.

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