| Resumo: | As part of the development of a new 4D Autopilot System for Unmanned Aerial Aircrafts (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path finding based on the aircraft’s own sensors data output, that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy Filter or the LQG/LTR, are available, the utter complexity of the new control system, together with the robustness and reliability required of such a system on an UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its performance. As such, a new nonlinear LQG/LTR algorithm, validated through computational simulation testing, is proposed on this paper. This research work was conducted in the Laboratory of Avionics and Control of the Department of Aerospace Sciences (DCA) at the Faculty of Engineering of the University of Beira Interior and supported by the Aeronautics and Astronautics Research Group (AeroG) of the Associated Laboratory for Energy, Transports and Aeronautics (LAETA).
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