Autonomous waypoint guidance for tilt-rotor unmanned aerial vehicle that has nacelle-fixed auxiliary wings

Abstract

The mathematical dynamics model of the tilt-rotor unmanned aerial vehicle (UAV) that has nacelle-fixed auxiliary wings (NFAWs) is presented based on computational fluid dynamics analysis using FLUENT and DATCOM. The advantage of the aerodynamic performance of the NFAW is compared to the performance of the original tilt-rotor UAV in a trim analysis as well as simulation. The inner loop and outer loop of the neural network controller are designed for the tilt-rotor and its NFAW variant. In order to improve the control performance of outer loop, pseudo-control hedging (PCH) is applied to the outer loop as well as the inner loop neural network control. The dynamic inversion on a linear model of the original tilt-rotor at hover conditions is used as a baseline. The sigma-pi neural network (SPNN) adaptation minimizes the error of the inversion model. This error typically occurs due to the use of an approximate tilt-rotor model for helicopter mode instead of the NFAW model throughout the flight envelope from helicopter to airplane mode. The waypoint navigation and the automatic hover guidance are applied to the most outer loop of the neural network controller for the autonomous flight, which consists of nacelle conversion and reconversion as well as automatic take-off and landing. The fast dynamic reference commands generated by the autonomous waypoint guidance are inputted to the outer loop control in order to make the PCH of the outer loop effective. Lastly, the nonlinear simulation results are compared under turbulent wind conditions, in which the NFAW is more negatively affected than the original tilt-rotor model.

Keywords

Neural network pseudo-control hedging dynamic inversion autonomous waypoint hover tilt-rotor nacelle-fixed auxiliary wings (NFAWs)

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