CAJ | 학술논문

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.
침대무인궤편대비행시존재적기동우합화외부간우등영향인소,제출기우“장-료궤”모식적신경망락자괄응역공제기설계방법.상세추도료기동우합영향,건립료완정적편대비행비선성수학모형,설계료비선성동태역공제률,제출료개진적 BP 신경망락산법,자괄응지핍근화재선보상동태역오차,개선료공제효과,병침대대형변환제출료간단유효적설계사상.방진표명,해공제기능유효실현편대대형적보지혹변환,공제계통결구구유량호적확충성.
@@@@In view of the effects of aerodynamic coupling and disturbance on unmanned aerial vehicles formation flight process, a design method of neural network adaptive inversion based on “leader-wing” mode is proposed. Firstly, considering the kinematics equations of the formation, the 3-D(three-dimensional) nonlinear mathematical model of the formation flight is established. The basic control law is developed in nonlinear dynamic inversion. Then the nonlinear dynamic inversion errors due to modeling error or disturbance are compensated adaptively on line by improved BP neural network. The performance of the control system is improved. A simple and effective design idea for formation change is proposed. Simulations demonstrate that the controller is effective and able to keep or change formation configuration rapidly, stably and exactly with no collision, and has a good anti-interference performance.