Situational-Command Motion Control of an Autonomous Unmanned Aerial Vehicle Searching for Forest Fires in an Unstable Air Environment

The major problems associated with the rapid detection of forest fire and smoke are considered based on the use of autonomous unmanned aerial vehicles for flying over and surveying certain areas. A method of searching for forest fires through a locally optimal flight route under conditions of uncertainty has been developed. We propose original provisions of fuzzy sets, which allow an autonomous unmanned aerial vehicle to build an effective information-analytical model of situational-command control for moving along a route obtained in real time. A model of knowledge representation and processing has been developed that allows the automatic synthesis of logical-transformational rules for situational-command motion control of the aircraft’s motion. It is shown that the proposed principle of building an information-analytical model makes it possible to reduce the complexity of selecting effective commands by significantly reducing the number of comparisons of the current situation with reference situations in the process of deriving solutions.