Abstract

Quadcopters (QCs) are used to solve a wide range of problems. However, their operating environment is characterized by high turbulence, which can lead to unintended impacts from external disturbances. The present research aimed to improve quadcopter stability under flight conditions associated with wind loads. To address this, a quadcopter control system using neural networks - a neural regulator - was developed. Mathematical modeling of quadcopter flight, both with and without a neural regulator, was conducted under external influences. Comparison criteria included the completion of transient processes and stabilization of flight altitude. The obtained data demonstrated that the use of a neural regulator in the control system reduces the time it takes to restore a predetermined flight path. This demonstrates the effectiveness of the proposed solution.

Keywords:Quadcopter; Quadcopter control system; Increasing quadcopter flight stability; Using neural networks in quadcopter control