Control of fixed-wing UAV at levelling phase using artificial intelligence

Abstract

The increase in the share of fly-by-wire and software controlled UAV is explained by the need to release the human-operator and the desire to reduce the degree of influence of the human factor errors that account for 26% of aircraft accidents. An important reason for the introduction of new control algorithms is also the high level of UAV failures due loss of communication channels and possible hacking. This accounts for 17% of the total number of accidents. The comparison with manned flights shows that the frequency of accidents of unmanned flights is 27,000 times higher. This means that the UAV has 1611 failures per million flight hours and only 0.06 failures at the same time for the manned flight. In view of that, this paper studies the flight autonomy of fixed-wing UAV at the levelling phase. Landing parameters of the UAV are described. They will be used to setup a control scheme for an autopilot based on fuzzy logic algorithm.