
科学技术与工程

中国技术经济学会
基于改进fal函数的四旋翼无人机姿态运动控制
Quadrotor UAV Attitude Motion Control Based on Improved fal Function
对于四旋翼无人机在姿态上的运动控制,目前主要方法是对自抗扰控制(active disturbance rejection control, ADRC)系统的应用。针对此系统在处理具有传感器噪声的复杂干扰时,以往的fal函数设计在应用上仍有许多缺陷。扩张状态观测器(extended state observer, ESO)在传统fal函数的作用下,其工作过程中存在观测的精度不足以及抖振发生率较高等问题。因此,在以往fal函数的基础上改进出了一种新型的非线性光滑tfal函数,并以此函数研究ESO,最后,将其他ADRC方法与此方法置于MATLAB/Simulink软件进行比较仿真,新设计的tfal函数表现出更好的收敛性。基于tfal设计的新型ESO,在误差估计和误差跟随性能上有着明显提升。同时相比于改进函数galn和传统函数fal,新型ESO下姿态自抗扰控制系统,其跟踪能力分别提升了2.3%和4%,抗干扰性能分别提升了50%和67%。
For the motion control of four-rotor UAV in attitude, the main method is the application of ADRC (active disturbance rejection control) system. For this system to deal with the complex interference with sensor noise, the previous fal function design still has many defects in application. Under the function of traditional fal function, the ESO(extended state observer) has the problems of insufficient observation accuracy and high chattering rate. Therefore, a new nonlinear smooth tfal function was improved on the basis of the previous fal function, and ESO was studied with this function. Finally, other ADRC methods were compared with this method in MATLAB/Simulink software, and the newly designed tfal function shows better convergence. The new ESO based on tfal design has obvious improvement in error estimation and error following performance. At the same time, compared with the improved function galn and the traditional function fal, the tracking capability of the new ESO attitude active disturbance rejection control system is improved by 2.3% and 4% respectively, and the anti-interference performance is improved by 50% and 67% respectively.
tfal function / quadcopters / attitude control
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