UAV flight path intelligent control based on annealing recurrent neural network extremum search algorithm

Abstract

Unmanned aerial vehicle (UAV) is an intelligent equipment, which is invented with the development of information technology and artificial intelligence technology. UAV is an intelligent equipment with the wireless remote control and brings its own power of unmanned aircraft, and it has small volume, and is easy to use and easy to carry. Due to its small size, it cannot carry large batteries, and with the shortage of poor load ability and short sustained flight distance. In order to overcome the shortage of the short flight distance of UAV, the research work about intelligent controlling for UAV flight path is studied in this paper, aiming to improve the level of UAV flight control and endurance. The characteristics of UAV and the algorithm are studied to guide the control and optimization for the UAV flight path design. The research results in this paper show that the algorithm plays a positive role in UAV flight path intelligent controlling, and it is helpful to improve its endurance. This research is significant as it explores intelligent control algorithms to optimize UAV flight paths, aiming to enhance their flight endurance and overall performance.