As science instruments on CubeSats become more sensitive to the attitude of the spacecraft, better methods must be employed to provide the accuracy needed to complete the planned mission. While systems that provide the accuracy required are available commercially, these solutions are not cost-effective, do not allow the design to be tailored to a specific mission, and most importantly, do not give students hand-on experience with attitude control actuators. This thesis documents the design, modeling, and simulation of a low-cost, student-fabricated, reaction wheel system for use in 3U CubeSat satellites. The entire design process for the development of this reaction wheel is based on fundamental design principles and can be replicated for either larger or smaller spacecraft as needed. Additionally, plans for bringing this design up to a prototyping and testing phase are outlined for continued use of this design in the Cal Poly CubeSat Laboratory.

Low-thrust interplanetary spacecraft trajectory optimization poses a uniquely difficult problem to solve because of the inherent nonlinearities of the dynamics and constraints as well as the large size of the search space of possible solutions. Tools currently exist that optimize low-thrust interplanetary trajectories, but these tools are rarely openly available to the public, and when they are available they require multiple interfaces between multiple different packages. The goal of this work is to present a new piece of low-thrust interplanetary spacecraft trajectory optimization software that is open-source and entirely self-contained so that more people can have access to the ability to design interplanetary trajectories. To achieve this goal, a gradient-descent based nonlinear programming method, called the interior point method, was used. The nonlinear programming method was chosen so that results from this work could be compared and contrasted with results from Spacecraft Trajectory Optimization Suite (STOpS), which uses heuristics to iterate towards a solution. Interior point methods are popular because of their ability to handle large amounts of equality and inequality constraints, which is a characteristic that is valuable for low-thrust interplanetary spacecraft trajectories. The software developed, Interior Point Optimizer (IP Optimizer), was then validated against test cases with known solutions to ensure that the software delivered the intended results. Lastly, a constraint satisfaction, a minimum-time, and a maximum-final-mass optimization problem were solved and compared with literature to illustrate the advantages of IP Optimizer and the methods it employs. For the constraint satisfaction problem, IP Optimizer was able to find a solution that exactly satisfied the desired terminal constraints whereas STOpS had an error of 2.29 percent. In this case, IP Optimizer had a reduced runtime of 15 percent compared to STOpS as well. When minimizing time for a spacecraft transfer, IP Optimizer improved upon the solution found by STOpS by 5.3 percent. The speed of convergence for IP Optimizer was almost twice as fast as STOpS for this case. These results show that IP Optimizer is faster than STOpS at converging on a solution and the solution it converges to has a better objective value and more accurately satisfies the terminal constraints than STOpS. Lastly, the maximum-final-mass problem resulted in an objective value that was only 0.5 percent lower than the value found in literature.

Once a satellite has completed its operational period, it must be removed responsibly in order to reduce the risk of impacting other missions. Geostationary Transfer Orbits (GTOs) offer unique challenges when considering disposal of spacecraft, as high eccentricity and orbital energy give rise to unique challenges for spacecraft designers. By leveraging small satellite research and integration techniques, a deployable drag sail module was analyzed that can shorten the expected orbit time of launch vehicle stages in GTO. A tool was developed to efficiently model spacecraft trajectories over long periods of time, which allowed for analysis of an object’s expected lifetime after its operational period had concluded. Material limitations on drag sail sizing and performance were also analyzed in order to conclude whether or not a system with the required orbital performance is feasible. It was determined that the sail materials and configuration is capable of surviving the expected GTO environment, and that a 49 m2 drag sail is capable of sufficiently shortening the amount of time that the space vehicles will remain in space.

ExoCube is the latest National Science Foundation (NSF) funded space weather CubeSat and is a collaboration between PolySat, Scientific Solutions Inc. (SSI), the University of Wisconsin, NASA Goddard and SRI International. The 3U will carry a mass spectrometer sensor suite, EXOS, in to low earth orbit (LEO) to measure neutral and ionized particles in the exosphere and thermosphere. Measurements of neutral and ion particles are directly impacted by the angle at which they enter EXOS and which leads to pointing requirements. A combination of a gravity gradient system with a momentum bias wheel is proposed to meet pointing requirements while reducing power requirements and overall system complexity. A MATLAB simulation of dynamic and kinematic behavior of the system in orbit is implemented to guide system design and verify that the pointing requirements will be met. The problem of achieving the required three-axis pointing is broken into four phases: detumbling, initial attitude acquisition, wheel spin-up, and attitude maintenance. Ultimately, this configuration for attitude control in a CubeSat could be applied to many future missions with the simulation serving as a design tool for CubeSat developers.

Hardware configurations, a control law, and a steering law are developed for a mixed hardware spacecraft that uses both control moment gyros and reaction wheels. Replacing one or more gyros in a spacecraft with a reaction wheel has potential for cost savings while still achieving much greater performance than using reaction wheels alone. Several simulated tests are run to compare the performance to a traditional all reaction wheel or all control moment gyro spacecraft, including analysis of failure modes and singular configurations. The mixed system performed similarly to all gyro systems, responding within 6% of the gyro system’s time for all nominal cases. It far exceeds the performance of reaction wheel systems, taking only a fourth of the time. It also handles failures better than reduced size gyro systems. As such, it can be an effective cost saving measure for certain satellite missions.

This thesis is concerned with electronic stability of an all-wheel drive electric vehicle with independent motors mounted in each wheel. The additional controllability and speed permitted using independent motors can be exploited to improve the handling and stability of electric vehicles. In this thesis, these improvements arise from employing a direct yaw moment control (DYC) system that seeks to adapt the understeer gradient of the vehicle and achieve neutral steer by employing a supervisory controller and simultaneously tracking an ideal yaw rate and ideal sideslip angle. DYC enhances vehicle stability by generating a corrective yaw moment realized by a torque vectoring controller which generates an optimal torque distribution among the four wheels. The torque allocation at each instant is computed by finding a solution to an optimization problem using gradient descent, a well-known algorithm that seeks the minimum cost employing the gradient of the cost function. A cost function seeking to minimize excessive wheel slip is proposed as the basis of the optimization problem, while the constraints come from the physical limitations of the motors and friction limits between the tires and road. The DYC system requires information about the tire forces in real-time, so this study presents a framework for estimating the tire force in all three coordinate directions. The sideslip angle is also a crucial quantity that must be measured or estimated but is outside the scope of this study. A comparative analysis of three different formulations of sliding mode control used for computation of the corrective yaw moment and an evaluation of how successfully they achieve neutral steer is presented. IPG Automotive’s CarMaker software, a high-fidelity vehicle simulator, was used as the plant model. A custom electric powertrain model was developed to enable any CarMaker vehicle to be reconfigured for independent control of the motors. This custom powertrain, called TVC_OpenXWD uses the torque/speed map of a Protean Pd18 implemented with lookup tables for each of the four motors. The TVC_OpenXWD powertrain model and controller were designed in MATLAB and Simulink and exported as C code to run them as plug-ins in CarMaker. Simulations of some common maneuvers, including the J-turn, sinusoidal steer, skid pad, and mu-split, indicate that employing DYC can achieve neutral steer. Additionally, it simultaneously tracks the ideal yaw rate and sideslip angle, while maximizing the traction on each tire[CB1] . The control system performance is evaluated based on its ability to achieve neutral steer by means of tracking the reference yaw rate, stabilizing the vehicle by means of reducing the sideslip angle, and to reduce chattering. A comparative analysis of sliding mode control employing a conventional switching function (CSMC), modified switching function (MSMC), and PID control (HSMC) demonstrates that the MSMC outperforms the other two methods in addition to the open loop system.

As the demand for air transportation is projected to increase, the environmental impacts produced by air travel will also increase. In order to counter the environmental impacts while also meeting the demand for air travel, there are goals and research initiatives that aim to develop more efficient aircraft. An emerging technology that supports these goals is the application of hybrid propulsion to aircraft, but there is a challenge in effectively exploring the performance of hybrid aircraft due to the time and money required for safe flight testing and due to the diverse design space of hybrid architectures and components. Therefore, computational tools that are capable of simulating the performance of a hybrid aircraft are incredibly useful in the design process and research space. Existing work on the simulation of hybrid aircraft focuses on modelling a specific hybrid propulsion system in a particular airframe, but it would be desirable to have a simulation tool that is not specific to one design. In this thesis, a simulation framework that can be easily configured for different types of hybrid structures and components is presented, and the simulator is validated using flight test data which demonstrates that the performance of the simulated aircraft is representative of a real aircraft. A design for a hybrid aircraft is also modelled and simulated over different flight profiles in order to study the performance of the hybrid propulsion system. Results indicate that the hybrid aircraft can be successfully simulated and demonstrate how the simulator can be used as a tool to study the best way to fly and operate a hybrid aircraft.

A light curve is a plot of brightness versus time of an object. Light curves are dependent on orbit, attitude, surface area, size, and shape of the observed object. Using light curve data, several analysis methods have been developed to derive these parameters. These parameters can be used for tracking orbital debris, monitoring satellite health, and determining the mission of an unknown spacecraft. This paper discusses the development, verification, and utilization of a tool that simulates light curve data. This tool models ground-based observations, space-based observations, self-shadowing geometry, tumbling debris, and controlled spacecraft. The main output from the tool is the pass prediction plot and the light curve plot. The author intends to publish the tool and supporting documents for future researchers to utilize. This will save researchers time developing their own models and the tool can act as a baseline for comparisons between analysis methods. For clarity, this paper does not develop nor implement a light curve analysis method, but rather creates a tool to simulate light curve observations and data. Each section of the tool was verified independently to ensure that the simulated light curves were correct. The tool was verified with STK, matlab, and simulink. It predicts the start and end times of passes, eclipses, and ground-site night cycles within 1% of the total event duration, when compared to STK. The attitude propagator predicts the attitude of the target with offsets less than 0.06 degrees on average and a maximum offset less than 0.6 degrees when compared to provided attitude code.

Attitude determination and estimation algorithms are developed and implemented in simulation for the Exocube satellite currently under development by PolySat at Cal Poly. A mission requirement of ±5˚ of attitude knowledge has been flowed down from the NASA Goddard developed payload, and this requirement is to be met with a basic sensor suite and the appropriate algorithms. The algorithms selected in this work are TRIAD and an Extended Kalman Filter, both of which are placed in a simulation structure along with models for orbit propagation, spacecraft kinematics and dynamics, and sensor and reference vector models. Errors inherent from sensors, orbit position knowledge, and reference vector generation are modeled as well. Simulations are then run for anticipated dynamic states of Exocube while varying parameters for the spacecraft, attitude algorithms, and level of error. The nominal case shows steady state convergence to within 1˚ of attitude knowledge, with sensor errors set to 3.5˚ and reference vector errors set to 2˚. The algorithms employed have their functionality confirmed with the use of STK, and the simulations have been structured to be used as tools to help evaluate attitude knowledge capabilities for the Exocube mission and future PolySat missions.

This graduate project compares legacy simplified general perturbation model (SGP4) code developed by NASA Johnson Space Center, Orbital Debris Program Office, to a recent public release of SGP4 code by David Vallado. The legacy code is a subroutine in a larger program named PREDICT, which is used to predict the location of orbital debris in GEO. Direct comparison of the codes showed that the new code yields better results for GEO objects, which are more accurate by orders of magnitude (error in meters rather than kilometers). The public release of SGP4 also provides effective results for LEO and MEO objects on a short time scale. The public release code was debugged and modified to provide instant functionality to the Orbital Debris Program Office. Code is provided in an appendix to this paper along with an accompanying CD. A User’s Guide is presented in Chapter 7.