基于CMAC的无人机紧密编队飞行控制研究

摘要

针对多无人机紧密编队飞行控制系统,提出一种基于小脑模型神经网络的编队飞行队形保持控制器.该控制器以飞行控制系统横向、纵向及垂直方向通道的动态误差作为小脑模型关节控制器(CMAC)的激励信号,并与常规的PID控制器相结合构成系统的复合控制.仿真结果表明:该控制器能够控制无人机编队,在定常运动和机动过程中都可以保持期望队形,且这种控制方法具有超调量较小,鲁棒性强,响应速度快,抗干扰能力强等优点.%A formation keeping controller based on CMAC is presented for multi-UAVs close formation flightrncontrol system. The controller combines the CMAC with PID controller and takes the dynamic errors from lateral,rnlongitudinal and vertical channels as input signals to the CMAC neural network. Simulation results show that underrnboth constant speed situations and maneuvering situations, the UAV formation with the designed controllerrnconverges to its desired formation and is of small overshoot, high robustness, fast response and strong anti-jammingrncapability.