Micro-Satellite Systems Design, Integration, and Flight.

Within the past decade, the aerospace engineering industry has evolved beyond the constraints of using single, large, custom satellites. Due to the increased reliability and robustness of commercial, off-the-shelf printed circuit board components, missions have instead transitioned towards deploying swarms of smaller satellites. Such an approach significantly decreases the mission cost by reducing custom engineering and deployment expenses. Nanosatellites can be quickly developed with a more modular design at lower risk. The Alpha mission at the Cornell University Space Systems Studio is fabricated in this manner. However, for the purpose of development, the initial proof of concept included a two-satellite system. The manuscript will discuss system engineering approaches used to model and mature the design of the pilot satellite. The two systems that will be primarily focused on are the attitude control system of the carrier nanosatellite and the radio frequency communications on the excreted femto-satellites. Milestones achieved include ChipSat to ChipSat communication, ChipSat to ground station communication, packet creation, error correction, appending a preamble, and filtering the signal. Other achievements include controller traceability/verification and validation, software rigidity tests, hardware endurance testing, Kane damper, and inertial measurement unit tuning. These developments matured the technological readiness level (TRL) of systems in preparation for satellite deployment.

Bio-Inspired Space Robotic Control Compared to Alternatives.

Controlling robots in space with necessarily low material and structural stiffness is quite challenging at least in part due to the resulting very low structural resonant frequencies or natural vibration. The frequencies are sometimes so low that the very act of controlling the robot with medium or high bandwidth controllers leads to excitation of resonant vibrations in the robot appendages. Biomimetics or biomimicry emulates models, systems, and elements of nature for solving such complex problems. Recent seminal publications have re-introduced the viability of optimal command shaping, and one recent instantiation mimics baseball pitching to propose control of highly flexible space robots. The readership will find a perhaps dizzying array of thirteen decently performing alternatives in the literature but could be left bereft selecting a method(s) deemed to be best suited for a particular application. Bio-inspired control of space robotics is presented in a quite substantial (perhaps not comprehensive) comparison, and the conclusions of this study indicate the three top performing methods based on minimizing control effort (i.e., fuel) usage, tracking error mean, and tracking error deviation, where 96%, 119%, and 80% performance improvement, respectively, are achieved.

Space Robot Sensor Noise Amelioration Using Trajectory Shaping.

Robots in space are necessarily extremely light and lack structural stiffness resulting in natural frequencies of resonance so low as to reside inside the attitude controller's bandwidth. A variety of input trajectories can be used to drive a controller's attempt to ameliorate the control-structural interactions where feedback is provided by low-quality, noisy sensors. Traditionally, step functions are used as the ideal input trajectory. However, step functions are not ideal in many applications, as they are discontinuous. Alternative input trajectories are explored in this manuscript and applied to an example system that includes a flexible appendage attached to a rigid main body. The main body is controlled by a reaction wheel. The equations of motion of the flexible appendage, rigid body, and reaction wheel are derived. A benchmark feedback controller is developed to account for the rigid body modes. Additional filters are added to compensate for the system's flexible modes. Sinusoidal trajectories are autonomously generated to feed the controller. Benchmark feedforward whiplash compensation is additionally implemented for comparison. The method without random errors with the smallest error is the sinusoidal trajectory method, which showed a 97.39% improvement when compared to the baseline response when step trajectories were commanded, while the sinusoidal method was inferior to traditional step trajectories when sensor noise and random errors were present.

Proposals for Surmounting Sensor Noises.

Classical and optimal control architectures for motion mechanics in the presence of noisy sensors use different algorithms and calculations to perform and control any number of physical demands, to varying degrees of accuracy and precision in regards to the system meeting the desired end state. To circumvent the deleterious effects of noisy sensors, a variety of control architectures are suggested, and their performances are tested for the purpose of comparison through the means of a Monte Carlo simulation that simulates how different parameters might vary under noise, representing real-world imperfect sensors. We find that improvements in one figure of merit often come at a cost in the performance in the others, especially depending on the presence of noise in the system sensors. If sensor noise is negligible, open-loop optimal control performs the best. However, in the overpowering presence of sensor noise, using a control law inversion patching filter performs as the best replacement, but has significant computational strain. The control law inversion filter produces state mean accuracy matching mathematically optimal results while reducing deviation by 36%. Meanwhile, rate sensor issues were more strongly ameliorated with 500% improved mean and 30% improved deviation. Inverting the patching filter is innovative but consequently understudied and lacks well-known equations to use for tuning gains. Therefore, such a patching filter has the additional drawback of having to be tuned through trial and error.

Inducing Performance of Commercial Surgical Robots in Space.

Pre-existing surgical robotic systems are sold with electronics (sensors and controllers) that can prove difficult to retroactively improve when newly developed methods are proposed. Improvements must be somehow "imposed" upon the original robotic systems. What options are available for imposing performance from pre-existing, common systems and how do the options compare? Optimization often assumes idealized systems leading to open-loop results (lacking feedback from sensors), and this manuscript investigates utility of prefiltering, such other modern methods applied to non-idealized systems, including fusion of noisy sensors and so-called "fictional forces" associated with measurement of displacements in rotating reference frames. A dozen modern approaches are compared as the main contribution of this work. Four methods are idealized cases establishing a valid theoretical comparative benchmark. Subsequently, eight modern methods are compared against the theoretical benchmark and against the pre-existing robotic systems. The two best performing methods included one modern application of a classical approach (velocity control) and one modern approach derived using Pontryagin's methods of systems theory, including Hamiltonian minimization, adjoint equations, and terminal transversality of the endpoint Lagrangian. The key novelty presented is the best performing method called prefiltered open-loop optimal + transport decoupling, achieving 1-3 percent attitude tracking performance of the robotic instrument with a two percent reduced computational burden and without increased costs (effort).

Bilinear Interpolation of Three-Dimensional Gain-Scheduled Autopilots.

Gain-scheduled autopilots have emerged as a dominant strategy to achieve adaptive control of coupled, non-linear engineering complexities, owing to an ability to adapt to changing operational conditions and uncertainties. This study focuses on utilizing bilinear interpolation of gain-scheduled autopilots, emphasizing enhanced system performance and robustness. Through a comprehensive investigation and comparative analysis using three disparate cases, advantages over conventional methods are revealed. Strengths and weaknesses of both simple and specialized variants (such as linear, and real-time gain-scheduling) are introduced. Three missile guidance case-studies utilize simulation time and miss distance figures of merit. Comparing the performance of bilinear interpolation and automatic instantiations to index-search, over comparable traveled distances, missile miss distances were improved 179% and 196% respectively with slightly improved computational burden.

Microsatellite Uncertainty Control Using Deterministic Artificial Intelligence.

This manuscript explores the applications of deterministic artificial intelligence (DAI) in a space environment in response to unknown sensor noise and sudden changes in craft physical parameters. The current state of the art literature has proposed the method, but only ideal environments, and accordingly this article addresses the literature gaps by critically evaluating efficacy in the face of unaddressed parametric uncertainties. We compare an idealized combined non-linear feedforward (FFD) and linearized feedback (FB) control scheme with an altered feedforward, feedback, and deterministic artificial intelligence scheme in the presence of simulated craft damage and environmental disturbances. Mean trajectory tracking error was improved over 91%, while the standard deviation was improved over 97% whilst improving (reducing) control effort by 13%.

Treatise on Analytic Nonlinear Optimal Guidance and Control Amplification of Strictly Analytic (Non-Numerical) Methods.

Optimal control is seen by researchers from a different perspective than that from which the industry practitioners see it. Either type of user can easily become confounded when deciding which manner of optimal control should be used for guidance and control of mechanics. Such optimization methods are useful for autonomous navigation, guidance, and control, but their performance is hampered by noisy multi-sensor technologies and poorly modeled system equations, and real-time on-board utilization is generally computationally burdensome. Some methods proposed here use noisy sensor data to learn the optimal guidance and control solutions in real-time (online), where non-iterative instantiations are preferred to reduce computational burdens. This study aimed to highlight the efficacy and limitations of several common methods for optimizing guidance and control while proposing a few more, where all methods are applied to the full, nonlinear, coupled equations of motion including cross-products of motion from the transport theorem. While the reviewed literature introduces quantitative studies that include parametric uncertainty in nonlinear terms, this article proposes accommodating such uncertainty with time-varying solutions to Hamiltonian systems of equations solved in real-time. Five disparate types of optimum guidance and control algorithms are presented and compared to a classical benchmark. Comparative analysis is based on tracking errors (both states and rates), fuel usage, and computational burden. Real-time optimization with singular switching plus nonlinear transport theorem decoupling is newly introduced and proves superior by matching open-loop solutions to the constrained optimization problem (in terms of state and rate errors and fuel usage), while robustness is validated in the utilization of mixed, noisy state and rate sensors and uniformly varying mass and mass moments of inertia. Compared to benchmark, state-of-the-art methods state tracking errors are reduced one-hundred ten percent. Rate tracking errors are reduced one-hundred thirteen percent. Control utilization (fuel) is reduced eighty-four percent, while computational burden is reduced ten percent, simultaneously, where the proposed methods have no control gains and no linearization.

Comparison of Deep Learning and Deterministic Algorithms for Control Modeling.

Controlling nonlinear dynamics arises in various engineering fields. We present efforts to model the forced van der Pol system control using physics-informed neural networks (PINN) compared to benchmark methods, including idealized nonlinear feedforward (FF) control, linearized feedback control (FB), and feedforward-plus-feedback combined (C). The aim is to implement circular trajectories in the state space of the van der Pol system. A designed benchmark problem is used for testing the behavioral differences of the disparate controllers and then investigating controlled schemes and systems of various extents of nonlinearities. All methods exhibit a short initialization accompanying arbitrary initialization points. The feedforward control successfully converges to the desired trajectory, and PINN executes good controls with higher stochasticity observed for higher-order terms based on the phase portraits. In contrast, linearized feedback control and combined feed-forward plus feedback failed. Varying trajectory amplitudes revealed that feed-forward, linearized feedback control, and combined feed-forward plus feedback control all fail for unity nonlinear damping gain. Traditional control methods display a robust fluctuation for higher-order terms. For some various nonlinearities, PINN failed to implement the desired trajectory instead of becoming "trapped" in the phase of small radius, yet idealized nonlinear feedforward successfully implemented controls. PINN generally exhibits lower relative errors for varying targeted trajectories. However, PINN also shows evidently higher computational burden compared with traditional control theory methods, with at least more than 30 times longer control time compared with benchmark idealized nonlinear feed-forward control. This manuscript proposes a comprehensive comparative study for future controller employment considering deterministic and machine learning approaches.

Autonomous Trajectory Generation Comparison for De-Orbiting with Multiple Collision Avoidance.

Over the past four decades, space debris has been identified as a growing hazard for near-Earth space systems. With limited access to space debris tracking databases and only recent policy advancements made to secure a sustainable space environment and mission architecture, this manuscript aims to establish an autonomous trajectory maneuver to de-orbit spacecrafts back to Earth using collision avoidance techniques for the purpose of decommissioning or re-purposing spacecrafts. To mitigate the risk of colliding with another object, the spacecraft attitude slew maneuver requires high levels of precision. Thus, the manuscript compares two autonomous trajectory generations, sinusoidal and Pontragin's method. In order to determine the Euler angles (roll, pitch, and yaw) necessary for the spacecraft to safely maneuver around space debris, the manuscript incorporates way-point guidance as a collision avoidance approach. When the simulation compiled with both sinusoidal and Pontryagin trajectories, there were differences within the Euler angle spacecraft tracking that could be attributed to the increased fuel efficiency by over five orders of magnitude and lower computation time by over 15 min for that of Pontryagin's trajectory compared with that of the sinusoidal trajectory. Overall, Pontryagin's method produced an autonomous trajectory that is more optimal by conserving 37.9% more fuel and saving 40.5% more time than the sinusoidal autonomous trajectory.

Micro Satellite Orbital Boost by Electrodynamic Tethers.

In this manuscript, a method for maneuvering a spacecraft using electrically charged tethers is explored. The spacecraft's velocity vector can be modified by interacting with Earth's magnetic field. Through this method, a spacecraft can maintain an orbit indefinitely by reboosting without the constraint of limited propellant. The spacecraft-tether system dynamics in low Earth orbit are simulated to evaluate the effects of Lorentz force and torques on translational motion. With 500-meter tethers charged with a 1-amp current, a 100-kg spacecraft can gain 250 m of altitude in one orbit. By evaluating the combined effects of Lorenz force and the coupled effects of Lorentz torque propagation through Euler's moment equation and Newton's translational motion equations, the simulated spacecraft-tether system can orbit indefinitely at altitudes as low as 275 km. Through a rare evaluation of the nonlinear coupling of the six differential equations of motion, the one finding is that an electrodynamic tether can be used to maintain a spacecraft's orbit height indefinitely for very low Earth orbits. However, the reboost maneuver is inefficient for high inclination orbits and has high electrical power requirement. To overcome greater aerodynamic drag at lower altitudes, longer tethers with higher power draw are required.

Virtual Sensoring of Motion Using Pontryagin's Treatment of Hamiltonian Systems.

To aid the development of future unmanned naval vessels, this manuscript investigates algorithm options for combining physical (noisy) sensors and computational models to provide additional information about system states, inputs, and parameters emphasizing deterministic options rather than stochastic ones. The computational model is formulated using Pontryagin's treatment of Hamiltonian systems resulting in optimal and near-optimal results dependent upon the algorithm option chosen. Feedback is proposed to re-initialize the initial values of a reformulated two-point boundary value problem rather than using state feedback to form errors that are corrected by tuned estimators. Four algorithm options are proposed with two optional branches, and all of these are compared to three manifestations of classical estimation methods including linear-quadratic optimal. Over ten-thousand simulations were run to evaluate each proposed method's vulnerability to variations in plant parameters amidst typically noisy state and rate sensors. The proposed methods achieved 69-72% improved state estimation, 29-33% improved rate improvement, while simultaneously achieving mathematically minimal costs of utilization in guidance, navigation, and control decision criteria. The next stage of research is indicated throughout the manuscript: investigation of the proposed methods' efficacy amidst unknown wave disturbances.

Dislocation-pipe diffusion in nitride superlattices observed in direct atomic resolution.

Device failure from diffusion short circuits in microelectronic components occurs via thermally induced migration of atoms along high-diffusivity paths: dislocations, grain boundaries, and free surfaces. Even well-annealed single-grain metallic films contain dislocation densities of about 1014 m-2; hence dislocation-pipe diffusion (DPD) becomes a major contribution at working temperatures. While its theoretical concept was established already in the 1950s and its contribution is commonly measured using indirect tracer, spectroscopy, or electrical methods, no direct observation of DPD at the atomic level has been reported. We present atomically-resolved electron microscopy images of the onset and progression of diffusion along threading dislocations in sequentially annealed nitride metal/semiconductor superlattices, and show that this type of diffusion can be independent of concentration gradients in the system but governed by the reduction of strain fields in the lattice.

Anisotropic Effects on the Thermoelectric Properties of Highly Oriented Electrodeposited Bi2Te3 Films.

Highly oriented [1 1 0] Bi2Te3 films were obtained by pulsed electrodeposition. The structure, composition, and morphology of these films were characterized. The thermoelectric figure of merit (zT), both parallel and perpendicular to the substrate surface, were determined by measuring the Seebeck coefficient, electrical conductivity, and thermal conductivity in each direction. At 300 K, the in-plane and out-of-plane figure of merits of these Bi2Te3 films were (5.6 ± 1.2)·10(-2) and (10.4 ± 2.6)·10(-2), respectively.

Epitaxial superlattices with titanium nitride as a plasmonic component for optical hyperbolic metamaterials.

Titanium nitride (TiN) is a plasmonic material having optical properties resembling gold. Unlike gold, however, TiN is complementary metal oxide semiconductor-compatible, mechanically strong, and thermally stable at higher temperatures. Additionally, TiN exhibits low-index surfaces with surface energies that are lower than those of the noble metals which facilitates the growth of smooth, ultrathin crystalline films. Such films are crucial in constructing low-loss, high-performance plasmonic and metamaterial devices including hyperbolic metamaterials (HMMs). HMMs have been shown to exhibit exotic optical properties, including extremely high broadband photonic densities of states (PDOS), which are useful in quantum plasmonic applications. However, the extent to which the exotic properties of HMMs can be realized has been seriously limited by fabrication constraints and material properties. Here, we address these issues by realizing an epitaxial superlattice as an HMM. The superlattice consists of ultrasmooth layers as thin as 5 nm and exhibits sharp interfaces which are essential for high-quality HMM devices. Our study reveals that such a TiN-based superlattice HMM provides a higher PDOS enhancement than gold- or silver-based HMMs.

Changing the academic culture: valuing patents and commercialization toward tenure and career advancement.

There is national and international recognition of the importance of innovation, technology transfer, and entrepreneurship for sustained economic revival. With the decline of industrial research laboratories in the United States, research universities are being asked to play a central role in our knowledge-centered economy by the technology transfer of their discoveries, innovations, and inventions. In response to this challenge, innovation ecologies at and around universities are starting to change. However, the change has been slow and limited. The authors believe this can be attributed partially to a lack of change in incentives for the central stakeholder, the faculty member. The authors have taken the position that universities should expand their criteria to treat patents, licensing, and commercialization activity by faculty as an important consideration for merit, tenure, and career advancement, along with publishing, teaching, and service. This position is placed in a historical context with a look at the history of tenure in the United States, patents, and licensing at universities, the current status of university tenure and career advancement processes, and models for the future.

Thermoelectric properties of HfN/ScN metal/semiconductor superlattices: a first-principles study.

Nitride-based metal/semiconductor superlattices are promising candidates for high-temperature thermoelectric applications. Motivated by recent experimental studies, we perform first-principles density functional theory based analysis of electronic structure, vibrational spectra and transport properties of HfN/ScN metal/semiconductor superlattices for their potential applications in thermoelectric and thermionic energy conversion devices. Our results suggest (a) an asymmetric linearly increasing density of states and (b) flattening of conduction bands along the cross-plane Γ-Z direction near the Fermi energy of these superlattices, as is desirable for a large power factor. The n-type Schottky barrier height of 0.13 eV at the metal/semiconductor interface is estimated by the microscopic averaging technique of the electrostatic potential. Vibrational spectra of these superlattices show softening of transverse acoustic phonon modes and localization of ScN phonons in the vibrational energy gap between the HfN (metal) and ScN (semiconductor) states. Our estimates of lattice thermal conductivity within the Boltzmann transport theory suggests up to two orders of magnitude reduction in the cross-plane lattice thermal conductivity of these superlattices compared to their individual bulk components.