Research Article
Research ona FuzzyAdaptive PIDControlMethod forFourRotor UAVControlSystem
@INPROCEEDINGS{10.1007/978-3-031-31733-0_39, author={Dai Wan and Simin Peng and Miao Zhao and Liang Peng and Yingying Yi and Hengyi Zhou}, title={Research ona FuzzyAdaptive PIDControlMethod forFourRotor UAVControlSystem}, proceedings={Smart Grid and Innovative Frontiers in Telecommunications. 7th EAI International Conference, SmartGIFT 2022, Changsha, China, December 10-12, 2022, Proceedings}, proceedings_a={SMARTGIFT}, year={2023}, month={5}, keywords={Four Rotor Unmanned Aerial Vehicle Fuzzy Control Proportion Integration Differentiation}, doi={10.1007/978-3-031-31733-0_39} }- Dai Wan
Simin Peng
Miao Zhao
Liang Peng
Yingying Yi
Hengyi Zhou
Year: 2023
Research ona FuzzyAdaptive PIDControlMethod forFourRotor UAVControlSystem
SMARTGIFT
Springer
DOI: 10.1007/978-3-031-31733-0_39
Abstract
Research on A Fuzzy Adaptive PID Control Method for Four Rotor UAV Control System With the continuous improvement of national living standards, people have higher and higher requirements for the reliability of power supply. The emergence of unmanned aerial vehicle inspection technology provides a new idea to solve the contradiction between the increasing equipment scale and the increasing inspection requirements. However, at present, the stability of the traditional proportion integration differentiation (PID) control system of the four rotor unmanned aerial vehicle (UAV) is not high enough. During the inspection, there are accidents of drones hitting power equipment from time to time. In view of the above problems, this paper studies the fuzzy adaptive PID control method to support the stable flight of four rotor UAV. The principle of fuzzy control is analyzed. The fuzzy control method and PID control method are deeply integrated. A fuzzy adaptive PID control system is designed. The universe and membership function of the relevant control parameters of the system are formulated. The tuning rules of fuzzy adaptive PID control system are formulated. Finally, the improved control system is simulated. The simulation results show that the fuzzy adaptive PID control algorithm can effectively improve the stability, reliability and emergency ability of UAV. This method can effectively improve the adaptability of UAV to perform complex missions in complex environments. The research results have guiding significance for expanding the application field of UAV.
