Electronic Science and Technology ›› 2021, Vol. 34 ›› Issue (10): 51-55.doi: 10.16180/j.cnki.issn1007-7820.2021.10.008

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Optimization Control of Quadrotor UAVs Based on Neural Network PID Algorithm

GUO Jie,JIN Hai,SHEN Xinge   

  1. School of Information Science and Technology,Zhejiang Sci-Tech University,Hangzhou 310018,China
  • Received:2020-06-30 Online:2021-10-15 Published:2021-10-18
  • Supported by:
    National Natural Science Foundation of China(51677172)


In this study, an attitude control algorithm based on neural network PID is proposed to solve the time-varying and nonlinear problems of the quadrotor UAVs system. The algorithm has the strong adaptive ability of PID algorithm and the strong anti-interference ability of neural network. Based on the establishment of the rigid body kinematics model and dynamics model of the quadrotor UAVs, the attitude simulation control model of the quadrotor UAV MATLAB-Simulink is built, and the control effect of the neural network PID control algorithm, traditional PID and cascade PID control algorithm on the three attitude angles of the UAVs is compared. The results show that compared with the other two control algorithms, the transition time of neural network PID control algorithm is reduced from 4 s to 1 s, and the static error of the system after output stabilization is only 0.5%, indicating that the neural network PID control algorithm has high control precision and better static and dynamic characteristics.

Key words: quadrotor, unmanned aerial vehicles, dynamics modeling, simulation, traditional PID, cascade PID, neural network PID, attitude control

CLC Number: 

  • TP273