飞机起落架自适应模糊神经PID控制方法的研究

Research on Adaptive Fuzzy Neural PID Control Method for Aircraft Landing Gear

针对传统PID控制与模糊PID控制的飞机起落架控制系统存在达不到理想控制精度以及控制速度的问题,提出一种基于模糊控制和神经网络的模糊神经PID控制算法。通过对起落架运动特点以及动力学相关的理论分析建立飞机起落架的运动模型,将此智能PID控制方法应用到飞机起落架的姿态控制系统中。利用MATLAB/Simulink软件进行仿真,并基于树莓派装置进行了起落架单腿实验。仿真和实验结果表明:模糊神经网络PID控制系统的响应速度和抗干扰能力相较于传统PID和模糊PID都有了较大的提升,系统稳定性更强。在飞机起落架控制系统中,应用模糊神经PID控制可进一步提升系统的响应速度,降低系统运动的惯性冲击,提高整体机构的稳定性。

Aiming at the problem that the aircraft landing gear control system controlled by traditional PID control and fuzzy PID control can not reach ideal control accuracy and control speed,a fuzzy neural PID control algorithm based on fuzzy control and neural network was proposed.The motion model of the aircraft landing gear was established by analyzing the motion characteristics of the land⁃ing gear and the relevant dynamics theoretical analysis.The intelligent PID control method was applied to the attitude control system of the aircraft landing gear.The simulation was carried out by MATLAB/Simulink software,and the landing gear single leg experiment was carried out based on the raspberry pie device.The simulation and experimental results show that the response speed and anti-interfer⁃ence ability of the fuzzy neural network PID control system are greatly improved compared with the traditional PID and fuzzy PID,and the system stability is stronger.In the aircraft landing gear control system,the application of fuzzy neural PID control can further improve the response speed of the system,reduce the inertial impact of the system motion,and improve the stability of the overall mechanism.