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针对无人机编队飞行时存在的气动耦合和外部干扰等影响因素,提出基于“长-僚机”模式的神经网络自适应逆控制器设计方法.详细推导了气动耦合影响,建立了完整的编队飞行非线性数学模型,设计了非线性动态逆控制律,提出了改进的BP神经网络算法,自适应地逼近和在线补偿动态逆误差,改善了控制效果,并针对队形变换提出了简单有效的设计思想.仿真表明,该控制器能有效实现编队队形的保持或变换,控制系统结构具有良好的扩充性.
Aiming at the influencing factors such as aerodynamic coupling and external interference in UAV flight formation, a neural network adaptive inverse controller design method based on “long-wing-machine ” mode is proposed. The influence of aerodynamic coupling is deduced in detail and a complete A non-linear dynamic mathematical model of formation flight is designed and a nonlinear dynamic inverse control law is designed. An improved BP neural network algorithm is proposed to adaptively approximate and compensate the dynamic inverse error online to improve the control effect. The simulation shows that the controller can effectively maintain or transform formation formation and control system structure has good scalability.