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This thesis presents research into the design of low-mass short backfire (SBF) antennas with enhanced performance. In the first section of this thesis, modern techniques that can be utilized to decrease the mass of the aluminum SBF antenna were introduced. Two different antenna designs were developed using additive manufacturing and perforation techniques. The first design was created by manufacturing the antenna using additive manufacturing techniques, resulting in a significant reduction in mass. Simulations were conducted on this design to analyze the impact of additive manufacturing on the antenna’s performance. The results indicated that the gain was significantly affected by high levels of surface roughness introduced during the manufacturing process. The second low-mass antenna design, the perforated 3D-printed SBF antenna, combines additive manufacturing and perforation techniques. Parametric studies were conducted on this antenna to determine the optimal size, shape, and arrangement of perforations to achieve the best mass reduction and gain results. Simulation studies found that the antenna with a 3x37 circular array of perforations on its rim, each with a radius of 4.5 mm, performed the best. The simulated results were validated by fabricating and measuring the antennas. The mass of the 3D-printed and perforated 3D-printed SBF antennas were approximately 70% and 80% lighter than the aluminum antenna, respectively, while maintaining minimal loss in gain. The second part of this thesis discusses the enhancement of gain and bandwidth in the SBF antenna. This was done by flaring the rim to increase the aperture size of the antenna. Simulation studies were conducted to examine the impact of rim flaring and rim height on antenna performance. The results of these studies indicate that this technique significantly improved both the gain and bandwidth of the antenna while having minimal effect on the cross-polarization ratio. To further enhance the bandwidth, an i

Estimators are critical to modern society and are present everywhere from automobile cruise control systems to satellite attitude determination and control. Ensuring that estimators produce reliable, trustworthy estimates is key to keeping users safe and systems functioning correctly. While many systems and metrics have been proposed to ensure estimator reliability, these come with disadvantages such as requiring time-consuming Monte Carlo simulations or encapsulating poorly performing estimators rather than addressing core issues. This dissertation examines the various factors that affect estimator reliability, specifically for Kalman Filter variants, and presents a new trustworthiness metric that quantifies a filter’s reliability without requiring Monte Carlo simulations: the covariance trust ratio (CTR). The reliability factors examined here include the type of Kalman filter used, whether a filter incorporates elements of the measurement source’s state, the type of process noise covariance model used, and the type of measurement sources used. To examine how these factors affect a Kalman filter’s reliability, this dissertation uses two existing methods from the literature, Normalized Estimate Error Squared (NEES) and Normalized Innovation Squared (NIS), in addition to the CTR. The impact of these reliability factors on a Kalman filter’s trustworthiness are demonstrated using a case study which explores how a spacecraft’s orbital state can be estimated using relative angle and range measurements of Resident Space Objects (RSOs). This case study shows that the CTR is an effective method for quantifying an estimator’s trustworthiness, highlights the effects of the various reliability factors studied here, and demonstrates that these factors can be quantitatively assessed to provide confidence in a filter’s trustworthiness. In order for new estimation methods to become commercially viable, they must demonstrate their reliability and trustworthiness to potential users.

Robotic missions to Mars and the Moon will increase over the next several decades. Rovers are a critical tool used in these missions, and they are constrained by challenges stemming from wheel slippage and slip-mitigation. This dissertation introduces three contributions to address these areas. First, I present a novel metric called \virtual slippage" to quantify wheel slippage by relating it to an effective change in wheel radius. Secondly, I study the feasibility of using auto and cross-correlation to detect wheel slippage. I found autocorrelation insufficient for slippage detection; I used cross-correlation and raw sensor data to train a neural network to detect slippage with an error of 0:07 to 0:1 classic slippage, or 0:02 to 0:5 cm using virtual slip on a 10 cm diameter wheel. Thirdly, I study the efficacy of asymmetrical wheel designs to mitigate and aid in escaping high-slip environments. By expanding and introducing the new defi nition of wheel slippage and new detection methods, this research paves the way for improved traction control on granular surfaces and improved maneuverability of extra-planetary rovers. I developed these tools to improve the success of future exploration missions for celestial bodies and improvements for terrestrial applications here on Earth.

Significant growth in the space industry has occurred in the last decade, largely thanks to technical advancements that have reduced the cost of select subsystems. For instance, structural and mechanical systems have seen cost reductions through more efficient manufacturing methods, less expensive materials, and improved simulations. Further cost reductions can still be obtained in the domain of space electronics. This domain continues to experience high costs due to the manufacturing methods and qualification processes required to certify radiation-hardened electronics. Well-defined processes to approve inexpensive commercial electronics for use in space are needed if the broader space electronics industry is to adopt using them in future designs, thus reducing the costs of spaceflight. This research first conducted two radiation effects screening campaigns to study the viability of using commercial parts in low Earth orbit. A statistical algorithm to aid in planning screening campaigns for commercial electronics is also provided. Finally, this research presents a generic test bench platform which is capable of accommodating various part families to facilitate rapid, cost-effective radiation effects screening. The data obtained from the research provided evidence to suggest that utilization of commercial parts in space is feasible. The algorithm provides methodology to aid in planning screening campaigns such that sample sizes can be selected based on a variety of factors, including part parameter control data. The test bench was developed to aid in conducting the two screening campaigns and provided a proof of concept that generic testing platforms utilizing plug-and-play functionality can be effective in enabling researchers to conduct cost-effective screening campaigns. Utilization of the screening algorithm and test bench platform will enable the space industry to effectively certify commercial off-the-shelf electronics for use in low Earth orbit.

Over generations, engineering faculty qualifications transitioned from practice to scientific theory basis, and engineering schools progressively shifted responsibility for instructing elements of practical design to industry. The result: a progressive erosion of practical design knowledge (design esoterica) in faculties and industry. Tolerancing based on ASME B4.2 Fits is one element of eroded mechanical engineering design esoterica and is now poorly understood in academe and industry. As a result, students and early-career mechanical design engineers are challenged to select appropriate Fit-types, and therefore to apply appropriate tolerances to their designs. Though unquantified, this leads to elevated industry costs associated with manufacturing and service. With thirty years in mechanical engineering design, over twenty years in the application and instruction of geometric dimensioning and tolerancing (GD&T) in industry, and six years instructing GD&T at the University of Manitoba, the author of this study has observed a general absence of tolerancing knowledge in industrial and academic environs. Recognizing the challenges of learning and teaching mechanical design esoterica in general, and dimensional tolerancing in particular, the author proposes a collection of artifacts as a first step in reintroducing, into mechanical engineering design, a functional understanding of tolerances, and tolerance magnitudes. Three visio and visio-haptic artifacts are designed for use in developing a cognizance of the clearance Fit-classes and the micron-scale tolerances associated with them. The artifact designs are based in the mechanical engineering design experience of the researcher. A qualitative self-study accompanies the engineering design study of the artifacts. A rhetorical Voice of a Design Companion is invoked as anecdotalist to convey the researcher’s design thinking, and to explore the evolution thereof. The scope of the engineering design study is limited to ide

Remote sensing technology is becoming a standard tool for Arctic studies to understand and preserve vulnerable ecosystems. A Ground Penetrating Radar (GPR) is a common tool used to study the change in ice properties, which can help reduce climate change effects. However, due to the GPR's large size and the Arctic's remote terrain, it is difficult to navigate GPRs in the Arctic. Flying the GPR using a drone provides a solution, but it requires the GPR to be suspended from the drone which can affect the drone's stability through the non-linear sway of the GPR. The non-linear effects may not be well captured by linear controllers and therefore require the implementation of a non-linear controller on the drone. In this thesis, I use a Light Detection and Ranging (LiDAR) sensor and an Extended Kalman filter to measure the position of the payload relative to the drone with an accuracy of 2 cm. Additionally, I design a feedback control system for the drone carrying a payload to compare the performance of a feedback integer-order Proportional-Integral-Derivative (IOPID) controller and fractional-order PID (FOPID) controller to minimize the sway of the payload. Results from simulation and experimental tests indicate that if optimally tuned, both the IOPID controller and FOPID controller (using the Oustaloup recursive filter) had a comparable performance for a non-linear drone-based cable-suspended system. Neither feedback controller provided the optimal performance to control the sway of the payload and a model-based control technique may be a better solution.

Seasonal velocity variations can significantly impact total energy delivered to microgrids produced by river hydrokinetic turbines. These turbines typically use a diffuser to increase the velocity at the rotor section, adding weight and increasing deployment and retrieval costs. There is a need for practical solutions to improve the capacity factor of such turbines for remote communities. Part of the solution is addressed by developing multiple turbine rotors that can be interchanged to match seasonal velocity variations and thereby eliminate the need for shrouds to simplify the design and reduce costs. The proposed approach employs different rotor sizes to address seasonal river velocity changes, modifying the turbine power curve to increase the yearly river turbine capacity factor. A turbine design that can be surfaced using boats available in remote communities is used to allow 2 blades rotor changes. BladeGen ANSYS Workbench is used to design the three rotors of decreasing size for free stream velocities of 1.6, 2.2, and 2.8 m/s. For each hydrokinetic turbine rotor, the 3D simulation is applied to reduce aerodynamic losses and target a coefficient of performance of up to 45%, by optimizing the blade shape and rotor aerodynamic parameters. Mechanical stress analyses determine the maximum displacement and blade stress for stainless steel and composite materials. Numerical results were compared to experimental results: the pressure coefficient against the tip speed ratio demonstrated good agreement with the experimental data. Based on the simulations, the three rotor efficiencies varied from 43% to 45% at a TSR of 4, the point at which the maximum pressure coefficient was observed in numerical and experimental results, while the power output varied from 5.4 to 5.6 kW for the three velocities investigated. Results show that it is possible to significantly increase turbine capacity factors by interchanging rotors to account for seasonal velocity variations in rivers.

Drone systems are being used everyday for many applications including delivery of goods and surveillance systems, which require a reliable navigation system to allow for a safe and successful mission. Global Navigation Satellite Systems have been the main means of navigation for decades, however, regions with poor GNSS coverage, such as the Arctic or urban centers, are challenging environments to navigate. In this thesis, the design and implementation of a low-cost portable beacon system that can provide position information using an extended Kalman filter (EKF) is presented. For the beacon system, an angle beacon prototype and two range beacon prototypes, one based on the received signal strength and the other based on the signal’s time of flight, were developed. The positioning performance of the EKF and beacons system in different scenarios was evaluated using Matlab simulations. The simulation results indicate that the range beacons offered the best positioning performance compared to the angle beacons or a mixture of both. Additionally, particle swarm optimization was used to optimally place an additional range/angle beacon, improving the overall system performance. Finally, the integrated system was tested in indoor and outdoor scenarios and the system output was compared with the ground truth data. The experimental tests resulted in a minimum error of 10.1 cm and 31.8 cm for indoor and outdoor tests, respectively. The steady state error was in orders of ≈ ±25 cm for the indoor tests and ≈ ±40 cm for the outdoor tests. Overall, the custom beacon designs provided reliable performance for drone navigation. With future hardware improvements, the system could be a viable option for low-cost portable navigation systems.

This thesis presents the development of a guidance and control system for a Self-Contained Orbit Determination Tool (SCOTT). SCOTT is designed to provide CubeSats with the capability to autonomously deorbit to meet the 25-year deorbiting guideline set by the United Nations Committee On the Peaceful Use of Outer Space (UNCOPUOS), as a means to mitigating the growing space debris problem. The SCOTT module is equipped with Sun sensors, magnetometer, gyroscope, and thrusters. This use of low-cost, simple sensors provides an autonomous, self-contained solution that does not require communication with spacecraft operators or other satellites. SCOTT's guidance system measures the Sun and magnetic field vectors over an orbit and uses the angle between the two measured vectors to determine the retrograde direction through a particle swarm optimization algorithm and a power spectral density analysis. SCOTT's control strategy consists of pointing the spacecraft's deorbit thrusters in the retrograde direction by controlling to prescribed Sun sensor and magnetometer measurements. The prescribed measurements represent the sensor readings that would be collected if the spacecraft was pointed in the correct direction for a retrograde burn. Using simulation, I developed an integrated guidance and control operational procedure that is able to self-assess its own optimization solution and autonomously carry out a deorbit maneuver. The results show that SCOTT is successfully able to determine its position, and perform a deorbit burn that maneuvers the spacecraft into a lower orbit that accelerates deorbit and ensures conformance to the deorbiting guideline.

In recent decades, the adoption of industrial robots in various manufacturing finishing processes such as sanding, deburring, and polishing has been on the rise. Robotic finishing processes require very close interaction with the workpiece, and forces are exerted by the robot’s end-effector on the workpiece during this interaction. The contact forces play a major role in the surface quality of the finished product and therefore need to be regulated to achieve the desired finish. However, when dealing with complex parts with free-form surfaces, such as the composite panel used in this thesis, controlling the contact forces would require more advanced force control methods. The aim of this research is to develop a hybrid force/position control methodology to enhance the quality and efficiency of the sanding process and control the forces applied on the workpiece. The first aim of this thesis is to develop a simulation model for the KUKA KR6 R700 used in this study. The model is developed in MATLAB Simulink using the forward and inverse kinematic model of the robot. The sanding motion is simulated with a visual representation, and the response and efficiency of the designed hybrid controller are tested. The forces and torques at the end-effector during the sanding motion are estimated. The estimated forces/torques are validated and used as feedback to the force control loop. The designed model can successfully estimate the forces at the end-effector using the Jacobian, and also control the contact forces and torques applied on the workpiece based on a defined setpoint. In the second part of this thesis, the designed hybrid force/position controller is experimentally implemented on a 6-axis robot. A 6-axis force/torque sensor is mounted at the end effector to measure the forces and torques applied on the workpiece when the robot performs the sanding motion. A PI controller is used for the force control loop, and a PD controller is used for closing the position loop. The

Spacecraft manoeuvres require reliable control systems for a successful mission. Testbeds play a critical role in testing spacecraft control systems prior to launch. However, limited availability, extreme costs, short endurance or limited reconfigurability prevent the current testbeds from being used by most researchers and space systems engineers. In this thesis, I present the Reconfigurable and Empirical Spacecraft Emulation Testbed (RESET) to test and validate spacecraft control systems in an indoor laboratory environment. This testbed takes advantage of a novel 6-DOF omnidirectional drone and Active Dynamic Emulator (ADE) method. The omnidirectional drone allows a 6-DOF independent translational and rotational controllability. The ADE is able to counteract the gravity of the earth and provides any other dynamic emulation required for the specific environment being simulated (such as air viscosity, custom gravity, or different vehicle mass or inertia). I introduce translational and rotational dynamic emulation for emulating mass, gravity and inertia. Then, I investigate the feasibility of the ADE and demonstrate its functionality for emulating different masses in real-time tests. Finally, I conclude that decreasing the frequency of the emulation loop and increasing the emulated mass leads to instability in the system. Next, I introduce a novel omnidirectional drone, which has a cubic structure and can accommodate 1U CubeSat in its core. I demonstrate the drone's 6-DOF independent rotational and translational capability with different flight tests in the STARLab's drone area. Test results show that the drone is able to change its attitude without changing its position and vice versa. In conclusion, the RESET can bring a low-cost, accessible and reconfigurable testbed for testing spacecraft control systems to the space industry.

This thesis addresses the nonlinear attitude control of an underactuated satellite equipped with only three magnetorquers. The problem involves stabilizing the sun-pointing 3U CubeSat in the presence of environmental perturbations and sensor noises from launch separation and deployment until the nominal mode. The sensors include a three-axis gyroscope, a three-axis magnetometer and a two-axis sun sensor. A detumbling and a proportional-derivative(PD) controller are applied to the underactuated dynamic system. Since a spin-stabilized configuration is naturally stable, a spin-stabilized mode is selected given the spin-axis is a major axis of inertia. Further, a power management strategy has been applied, which requires a small amount of control effort. The proposed linear control law achieves attitude convergence for three-axis stability within the 0.18 degrees attitude error and 1 deg/s spin rate norm. The design has been implemented using a high fidelity real-time simulation in Simulink/MATLAB while considering the environmental effects to study the in-orbit behaviour and the effectiveness of the system's stability in overcoming the disturbance torques, including gravity gradient torque, residual dipole torque, dynamic uncertainties, and sensors noise. Since sun sensors do not provide any measurements in the eclipse, an Extended Kalman Filter (EKF) is embedded in the simulation to give estimates of the attitude angles in the eclipse based on gyroscope measurements. The estimator benefits from a dimension reduction technique to increase the estimation reliability and reduce the onboard computational and power usage. Numerical simulations successfully corroborate the effectiveness of the controller and the estimator.

This thesis presents an automated ground-based anomaly detection system for an attitude dynamics system of a small satellite. In a space mission, a ground station works as the operation center to communicate and monitor the satellite. Human operators are required to stay at the ground station at all times to collect, track, and analyze the performance of the satellite. With the growing popularity of the Artificial Intelligence (AI) application in recent years, processes relating to data collection, transmission, and analysis have been replaced by machine learning which reduces human labour, expense and time, whereas shortcomings in the traditional human expert systems are improving, and applications to space systems fault detection are now possible. Therefore, in this research, machine learning algorithms were applied to accomplish the proposed anomaly detection system. The detection system aimed to detect subtle failures in the spacecraft's attitude dynamics system, mainly in the reaction wheel subsystem, by only learning from nominal behavioural data from the spacecraft. The system was developed from a small satellite attitude dynamics control system using reaction wheels that may exhibit bearing failures. There were two types of anomaly detection systems introduced, including a two-sided learning anomaly detection system and a one-sided learning anomaly detection system. For this study, I first developed the two-sided learning anomaly detection system using the Logistic Regression (LR) method, which provided a background of how the training process would be undertaken using a machine learning method. By learning from both nominal and failure behaviours from the satellite, the system was expected to detect small reaction wheel friction failures. Then, the one-sided learning anomaly detection system was built by only learning from nominal behaviours from the satellite and was expected to detect the same reaction wheel failures. The methods used to develope the one

Carbon fiber and fiberglass composite panels are commonly used in the aerospace and automotive industries. During the manufacturing process, composite panels undergo surface treatment processes such as priming and coating. For coating layers to adhere strongly to the surface, the part surface must be free of any contamination such as grease. Detection and removal of contamination is an important step in the manufacturing of composite panels, particularly in the aerospace industry. This thesis develops a novel vision-based framework to enable fully automated inspection and robotic abrasion of free-form composite panels. The first aim of the thesis is to automatically locate arbitrarily placed composite panels within the robot workplace. The proposed method employs iterative closest point (ICP) registration technique for locating the part in the robot cell. An additional module based on vision-based error correction is developed in the thesis for improving the accuracy of part localization. The proposed part localization technique eliminates the need for manual calibration of part placement in each robot cycle. The ASTM-F22 water-break test is widely used for detecting hydrophobic contamination on a surface. As the second aim in this thesis, vision-based algorithms are developed to allow for the automated detection (inspection) of hydrophobic contamination during the water-break test. The developed vision-based algorithms can successfully detect the layer of hydrophobic contamination on the free-form panel. The third aim of this thesis is to automatically generate robotic abrasion tool paths to remove detected contamination. In the proposed framework, the panel surface is divided into multiple grids. The point clouds of each grid are first used to reconstruct continuous parametric B-spline surfaces. B-spline surfaces are then used to make an abrasion tool path for each grid. The developed vision-based inspection algorithm determines which grids contain contamination a

This thesis evaluates the feasibility of an embedded antenna multifunctional structure (MFS) for spacecraft applications. The increasing commercialization and miniaturization of space missions call for versatile subsystems that make efficient use of limited spacecraft volumes. This research investigates a design for a microstrip patch antenna with an SU-8 photoresist substrate on a hybrid composite structural panel comprised of aluminum, carbon fibre composite (CFC) and polyethylene fibre composite (PFC) materials. While the proposed design does not outperform high-powered antennas such as reflectors, they can be utilized as secondary communication antennas for tracking, telelemetry and command (TT&C). In order to design and model the antenna in ANSYS HFSS electromagnetic simulations, all of the materials are characterized first. I performed a series of tests using parallel plate and microstrip devices to extract their electrical properties. After modelling and design, a manufacturing process for the substrate is optimized to work around the thermal constraints of the composite materials. The antenna is then deposited on top using a stencil and copper deposition methods. During the connector attachment process, the antenna prototype was subjected to rapid temperature changes which caused the SU-8 substrate layer and copper patch to crack in several places. The cracking introduced air gaps between the substrate and aluminum ground plane, and the microstrip patch was ammended by placing copper tape on top. After such repairs, the antenna prototype is then measured at an operational frequency of 2.5 GHz, with a -10 dB bandwidth of 60 MHz, and a peak gain of 1.45 dB. These results were followed by an investigation of various loss mechanisms. Although the resulting performance of the MFS antenna did not meet the expectations and criteria, there are still potential applications with my recommendations for future work in this research area that can improve the feasibility