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为了提高多旋翼无人飞行器机载光电平台的扰动补偿能力,实现机载光电平台的稳定跟踪控制,提出一种基于改进扰动观测器和径向基函数(RBF)神经网络逼近的复合补偿控制方法。首先,对现有扰动观测器结构进行改进,构建基于速度信号的改进型扰动观测器,并分析了干扰补偿能力和稳健性;然后,利用RBF神经网络的函数逼近性质解决非线性未知扰动的补偿问题;最后,基于Lyapunov稳定性原理设计出复合补偿控制结构。实验结果表明,机载光电平台的扰动得到有效补偿。该补偿控制方法具有较高的稳定精度和跟踪控制性能,满足多旋翼无人飞行器机载光电平台的稳定控制要求。
In order to improve the disturbance compensation ability of the multi-rotor UAV airborne photoelectric platform and realize the stable tracking control of the airborne electro-optical platform, a complex compensation control method based on improved perturbation observer and radial basis function (RBF) neural network approximation . Firstly, the structure of the existing disturbance observer is improved, an improved disturbance observer based on the velocity signal is constructed, and the ability of disturbance compensation and robustness are analyzed. Then, the function approximation property of RBF neural network is used to solve the compensation of nonlinear unknown disturbance Problem; Finally, the composite compensation control structure is designed based on the Lyapunov stability principle. Experimental results show that the disturbance of the airborne optical platform is effectively compensated. The compensation control method has high stability and tracking control performance to meet the stability control requirements of multi-rotor UAV airborne optical platform.