Open AccessResearch of UAV Flight Control Algorithm Based on Improved Fuzzy Neuron
Author(s) -
Haibin Liu,
Shuhua Fang,
Chenyu Yang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1544/1/012151
Subject(s) - pid controller , robustness (evolution) , control theory (sociology) , matlab , computer science , fuzzy logic , algorithm , fuzzy control system , control engineering , engineering , control (management) , artificial intelligence , temperature control , biochemistry , chemistry , gene , operating system
UAV flight control systems have the characteristics of non-linear, multi-variable, and strong coupling. Traditional PID control algorithms have many problems in complex flight environments, such as large adjustable parameters, poor robustness, and slow convergencein. Due to the defects of traditional PID control algorithm, this paper proposes an improved PID control algorithm based on fuzzy neurons. The modified fuzzy neuron is used to modify the traditional PID control algorithm. Through Matlab experimental simulation, it is proved that the algorithm has a significant improvement in response speed, robustness, accuracy and anti-interference compared with the traditional PID algorithm.