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Fuzzy Neural Network PID Control of Quadrotor Unmanned Aerial Vehicle Based on PSO-GA Optimization

  • Xia LiEmail author
  • Shuaihua Zhang
  • Fang Zheng
  • Bingyuan Wang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 582)

Abstract

Aiming at the characteristics of strict nonlinearity, strong coupling and instability of quadrotor UAV, a fuzzy neural network PID controller based on a hybrid particle swarm algorithm (PSO-GA) is designed. The global optimization ability is improved by integrating the crossover and mutation operations of the genetic algorithm into the particle swarm optimization algorithm. In this paper, the initial value of each parameter of fuzzy neural network is optimized offline by PSO-GA algorithm and adjusted online by gradient descent method. The optimized PID controller can be applied to the attitude control of the quadrotor UAV. The simulation results show that the system has faster response speed, stronger robustness, less steady-state error and stronger tracking ability than the traditional control algorithm.

Keywords

Quadrotor UAV Fuzzy neural network PSO-GA PID control 

References

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Xia Li
    • 1
    Email author
  • Shuaihua Zhang
    • 1
  • Fang Zheng
    • 1
  • Bingyuan Wang
    • 1
  1. 1.College of Electronic Information and AutomationCivil Aviation University of ChinaTianjinChina

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