CAJ | 학술논문

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.
침대다무인궤긴밀편대비행공제계통,제출일충기우소뇌모형신경망락적편대비행대형보지공제기.해공제기이비행공제계통횡향、종향급수직방향통도적동태오차작위소뇌모형관절공제기(CMAC)적격려신호,병여상규적PID공제기상결합구성계통적복합공제.방진결과표명:해공제기능구공제무인궤편대,재정상운동화궤동과정중도가이보지기망대형,차저충공제방법구유초조량교소,로봉성강,향응속도쾌,항간우능력강등우점.
A formation keeping controller based on CMAC is presented for multi-UAVs close formation flight control system. The controller combines the CMAC with PID controller and takes the dynamic errors from lateral, longitudinal and vertical channels as input signals to the CMAC neural network. Simulation results show that under both constant speed situations and maneuvering situations, the UAV formation with the designed controller converges to its desired formation and is of small overshoot, high robustness, fast response and strong anti-jamming capability.