Research on Attitude Control System of Four-Rotor Aircraft

With the characteristics of simple mechanical structure, light weight, and low R & D cost, the four-rotor aircraft is widely used in many fields at present. Aiming at attitude control accuracy and anti-jamming of the four-rotor aircraft, it has been one of the hot topics. In order to improve the attitude control accuracy of the four-rotor aircraft and the resistance of it to the external environment, this paper analyzes the dynamic model of the four-rotor aircraft in detail, optimizes the RBF neural network by improving the particle swarm algorithm, and uses the neural network to learn to achieve adaptive adjustment of control parameters in PID controller. Then, based on a three-dimensional scene, the simulation platform is built for simulation testing and result analysis in this paper. From experimental results, it shows that the designed control algorithm in this paper not only enhances the anti-jamming ability of the four-rotor aircraft, but also improves its control accuracy. It has a good application effect.