【摘要】 针对四旋翼无人机姿态控制过程中模型不确定及外部扰动问题，设计了一种自抗扰控制的姿态控制器。将模糊控制方法与传统的自抗扰控制理论相结合，增加了一个集模糊化、模糊推理和清晰化为一体的模糊控制单元，采用改进天牛须算法整定自抗扰控制器参数，提高了参数整定效率。为解决fal函数拐点处不平滑，易产生小幅抖振以及误差较大时系统增益较大等问题，引入了改进的yfal函数替代扩张状态观测器中的fal函数，并对改进后的状态观测器进行了收敛性判断。仿真结果表明，改进后的自抗扰控制器具有更快的响应速度和抗干扰能力。更多还原

【Abstract】 To overcome the issues associated with model uncertainty and external disturbances during the attitude control of a quadcopter UAV, this paper designs a quadcopter attitude controller based on self-disturbance rejection control. It integrates fuzzy control technology with traditional self-disturbance rejection control, incorporating a fuzzy control unit that combines fuzzification, fuzzy inference, and defuzzification. Furthermore, an improved beetle antennae search algorithm is employed for parameter tuning of the self-disturbance rejection controller, enhancing parameter tuning efficiency. To address the issues related to the non-smoothness of the fal function at its turning point, which leads to system oscillations and the problem of high gain in cases of significant errors, an improved yfal function is introduced to replace the fal function within the extended state observer. The convergence of this improved observer is also verified. Our simulation results demonstrate the enhanced self-disturbance rejection controller exhibits fairly faster response and improved disturbance-resistance capabilities.更多还原