ETD Collection

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    Drone-based delivery of clinical specimens in a rural enviroment : a feasibility study
    (2017) Berman, Joshua Shlomo
    A framework is developed for the implementation of an autonomous drone-based delivery system. The concept stems from the need for more efficient methods of clinical transport in underdeveloped regions. A case study of a region in Mpumalanga investigates the requirements of the delivery system and scale of the intended solution. The travelling salesman problem (TSP) is used to determine that a region with 19 request points can be serviced by a single drone with a 30 minute flight range and 2 - 4 kg payload capacity. A notional region containing 20 clinics and one laboratory is used to simulate scenarios with dynamic request points using a reward-based inspection algorithm. Delivery routes are optimised based on global conditions. An evaluation of the inspection algorithm resulted in the drones averaging 103.53 km in 139.21 minutes. A framework is thus developed which allows for a theoretical scenario analysis for future implementations. The specimen turnaround time from clinic to laboratory is assessed using 120 scenarios of varying wind speed and request generation rates. In wind conditions similar to that observed in Mpumalanga (5 - 25 km/h), the drone averaged 93.94 minutes per request. At a request rate of two requests per hour the drone delivered an average of 180 samples generated in the first nine hours of simulation. At a request rate of one request every 6 hours the drone averaged 29 samples. Future work could include an in depth study of seasonal request rates and weather pattern data in order to influence the path of the drone for a further optimised approach as well as the development of more advanced optimisation algorithms.
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    Aerodynamic parameter identification for an unmanned aerial vehicle
    (2016) Padayachee, Kreelan
    The present work describes the practical implementation of systems identification techniques to the development of a linear aerodynamic model for a small low-cost UAV equipped with a basic navigational and inertial measurement systems. The assessment of the applicability of the techniques were based on determining whether adequate aerodynamic models could be developed to aid in the reduction of wind tunnel testing when characterising new UAVs. The identification process consisted of postulating a model structure, flight test manoeuvre design, data reconstruction, aerodynamic parameter estimation, and model validation. The estimators that were used for the post-flight identification were the output error maximum likelihood method and an iterated extended Kalman filter with a global smoother. SIDPAC and FVSysID systems identification toolboxes were utilised and modified where appropriate. The instrumentation system on board the UAV consisted of three-axis accelerometers and gyroscopes, a three-axis vector magnetometer and GPS tracking while data was logged at 25 Hz. The angle of attack and angle of sideslip were not measured directly and were estimated using tailored data reconstruction methods. Adequate time domain lateral model correlation with flight data was achieved for the cruise flight condition. Adequacy was assessed against Theil’s inequality coefficients and Theil’s covariance. It was found that the simplified estimation algorithms based on the linearized equations of motion yielded the most promising model matches. Due to the high correlation between the pitch damping derivatives, the longitudinal analysis did not yield valid model parameter estimates. Even though the accuracy of the resulting models was below initial expectations, the detailed data compatibility analysis provided valuable insight into estimator limitations, instrumentation requirements and test procedures for systems identification on low-cost UAVs.