International audienceThis paper addresses the implementation of a predictive control strategy for Unmanned Air Vehicles in the presence of bounded disturbances. The goal is to prove the feasibility of such a real-time optimization-based control design and to demonstrate its tracking capabilities for the nonlinear dynamics with respect to a reference trajectory which is pre-specified via differential flatness. In order to benefit from the computational advantages of the linear predictive control formulations, an off-line linearization strategy of the nonlinear model of the vehicle along the flat trajectory is employed. The proposed method exhibits effective performance validated through software-in-the-loop simulations and real flight tests on different Unmanned Aerial Vehicles (UAVs)
We present a survey of atmospheric flow field phenomena models. The studied models are selected for their potential use towards extended aircraft endurance. This work describes several flow field phenomena, i.e., air flow currents and flow velocity variations. In particular, we discuss wind shear, thermal updrafts, and gusts. We study several wind shear models, such as the Surface, Layer, and Ridge Wind Shear models, comparing their characteristics. We also describe and compare thermal updraft models, such as the Chimney and the Bubble Thermal models. To close, we review different gust models. Throughout this work, we studied several existing models, but we also introduce new ones and improved versions of existing ones. The Bubble Thermal, Layer Wind Shear, and the Ridge Wind Shear models are examples of the new models presented. Furthermore, we present the Chimney Thermal model improvements, which take into account the phenomenon interaction with the prevailing winds.
The paper addresses the problem of vehicle rollover avoidance using reference governors applied to modify the driver steering input in vehicles with an active steering system. Several reference governor designs are presented and tested with a detailed nonlinear simulation model. The vehicle dynamics are highly nonlinear for large steering angles, including the conditions where the vehicle approaches a rollover onset, which necessitates reference governor design changes. Simulation results show that reference governor designs are effective in avoiding rollover. The results also demonstrate that the controllers are not overly conservative, adjusting the driver steering input only for very high steering angles.
This paper presents atmospheric Shear Wind phenomena models and develops a Particle Filter estimator to characterize the phenomena. We describe a model for the Surface Shear Wind and another for the Layer Shear Wind. The models are described and adjusted for Besian estimation. A Particle Filter was implemented and tested in simulation for Surface Shear Wind parameter estimation. The estimator was idealized to be used by small Unmanned Aerial Vehicles (UAVs). The implemented Particle Filter estimates the surrounding flow field with a small number of variables, and as such, low memory requirements.
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