Aerospace Engineering Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1655

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Start date: 2010End date: 2019

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Now showing 1 - 5 of 5
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    Feedback motion replanning during high-stakes scenario
    (2019) M Jaffar, Mohamed Khalid; Otte, Michael
    This paper proposes a novel algorithm for a quadrotor to replan its motion in the event of one, two or three rotor loss. Further, during the course of its replanned trajectory, the MAV avoids collision with static obstacles including the ground.
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    Control of a Heavy-Lift Robotic Manipulator with Pneumatic Artificial Muscles
    (MDPI, 2014-04-24) Robinson, Ryan M.; Kothera, Curt S.; Wereley, Norman M.
    Lightweight, compliant actuators are particularly desirable in robotic systems intended for interaction with humans. Pneumatic artificial muscles (PAMs) exhibit these characteristics and are capable of higher specific work than comparably-sized hydraulic actuators and electric motors. The objective of this work is to develop a control algorithm that can smoothly and accurately track the desired motions of a manipulator actuated by pneumatic artificial muscles. The manipulator is intended for lifting humans in nursing assistance or casualty extraction scenarios; hence, the control strategy must be capable of responding to large variations in payload over a large range of motion. The present work first investigates the feasibility of two output feedback controllers (proportional-integral-derivative and fuzzy logic), but due to the limitations of pure output feedback control, a model-based feedforward controller is developed and combined with output feedback to achieve improved closed-loop performance. The model upon which the controller is based incorporates the internal airflow dynamics, the physical parameters of the pneumatic muscles and the manipulator dynamics. Simulations were performed in order to validate the control algorithms, guide controller design and predict optimal gains. Using real-time interface software and hardware, the controllers were implemented and experimentally tested on the manipulator, demonstrating the improved capability.
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    Impact of Nanowires on the Properties of Magnetorheological Fluids and Elastomer Composites
    (INTECH, 2010-02) Bell, Richard C.; Zimmerman, Darin T.; Wereley, Norman M.
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    Evaluation of Particle Clustering Algorithms in the Prediction of Brownout Dust Clouds
    (2011-08) Govindarajan, Bharath; Leishman, Gordon
    A study of three Lagrangian particle clustering methods has been conducted with application to the problem of predicting brownout dust clouds that develop when rotorcraft land over surfaces covered with loose sediment. A significant impediment in performing such particle modeling simulations is the extremely large number of particles needed to obtain dust clouds of acceptable fidelity. Computing the motion of each and every individual sediment particle in a dust cloud (which can reach into tens of billions per cubic meter) is computationally prohibitive. The reported work involved the development of computationally efficient clustering algorithms that can be applied to the simulation of dilute gas-particle suspensions at low Reynolds numbers of the relative particle motion. The Gaussian distribution, k-means and Osiptsov's clustering methods were studied in detail to highlight the nuances of each method for a prototypical flow field that mimics the highly unsteady, two-phase vortical particle flow obtained when rotorcraft encounter brownout conditions. It is shown that although clustering algorithms can be problem dependent and have bounds of applicability, they offer the potential to significantly reduce computational costs while retaining the overall accuracy of a brownout dust cloud solution.