Many beneficial civilian applications of commercial and public small unmanned aircraft systems (sUAS) in low-altitude uncontrolled airspace have been proposed and are being developed. Associated with the proliferation of civil applications for sUAS is a paradigm shift from single-UAS visual operations in restricted airspace to multi-UAS beyond visual line of sight operations with increasing use of autonomous systems and operations under increasing levels of urban development and airspace usage. Ensuring the safety of sUAS operations requires an understanding of associated current and future hazards. This is challenging for sUAS operations due to insufficient mishap (accident and incident) reporting for sUAS and the rapid growth of new sUAS applications (or use cases) that have not yet been implemented. These applications include imaging, construction, photography and video, precision agriculture, security, public safety, mapping and surveying, inspections, environmental conservation, communications, parcel delivery, and humanitarian efforts such as delivery of medical supplies in developing nations. This paper will summarize research results in the identification of: 1.) Current hazards through the analysis of sUAS mishaps; and 2.) Future hazards through the analysis of a collection of sUAS use cases. The mishaps analysis will include the identification of mishap precursors and an analysis of their individual contributions to the mishaps as well as an analysis of worst-case hazards combinations and sequences. The future hazards are identified through an assessment and categorization of use cases for sUAS, the identification of associated paradigm shifts in terms of operations and new vehicle systems (both cross-cutting and for specific use case categories), the determination of future potential hazards (relative to the vehicle, ground control station, operations, and UTM system) arising from these paradigm shifts, and future potential impacts and outcomes (relative to the vehicle, other vehicles, people, ground infrastructure, and the environment). Key findings from these analyses are also summarized. The analysis results are then used to develop a set of combined (current and future) hazards for assessing risk.

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A key feature of all of the recent well-recorded severe pilot-induced oscillations (PIOs) is the presence of actuator rate limiting. As part of attempts to develop a comprehensive understanding of PIO phenomena, the results of an effort focused on improved understanding and analysis of actuator rate limiting are presented. For this effort describing functions were used in concert with modern computer simulation techniques to quantify the added phase lag, magnitude reduction, and bandwidth reduction of a rate-limited actuator in terms of the input and actuator design parameters. The results and inverse describing function techniques are then employed to analyze the limit cycle potential of a system that is essentially linear except for the series nonlinearity. The well-documented X-15 landing are PIO is used to exemplify these analysis techniques. From this example it is shown that these techniques can be used to provide a prediction of the limit cycle or PIO frequency. Nomenclature A= maximum amplitude of actuator command input sine wave a 1 ; b 1 = Fourier fundamental coef cients e = closed-loop actuator model error e L = rate limit saturation point K p = pilot gain q = pitch rate s = Laplace operator T = linear system time constant T NL = nonlinear system indicial response time constant V L = rate limit ± = effector output surface position P ± = actuator rate ± c = actuator input position command ± h = horizontal stabilizer angle µ = pitch attitude µ c = pitch attitude command µ e = pitch attitude error ¿ pµ = pitch attitude phase delay Á i = phase shift of actuator command input sine wave ! a = linear actuator close-loop bandwidth (or linear actuator gain) ! 0 a = nonlinear closed-loop actuator bandwidth (or effective nonlinear actuator gain) ! BWµ = pitch attitude airplane bandwidth frequency ! i = frequency of actuator command input sine wave ! u = linear system unstable frequency

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Vehicle handling and stability are significantly affected by inertial properties including moments of inertia and center of gravity location. This paper will present an analysis of the NHTSA Inertia Database and give regression equations that approximate moments of inertia and center of gravity height given basic vehicle properties including weight, width, length and height. The handling and stability consequences of the relationships of inertial properties with vehicle size will be analyzed in terms of previously published vehicle dynamics models, and through the use of a nonlinear maneuvering simulation.

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