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针对动力翼伞精确数学模型难以获得,系统输入输出关系耦合复杂等特点,建立动力翼伞8自由度动力学模型,设计由静态神经网络和积分器组成的动态神经网络,利用神经网络的逼近能力和动态逆控制方法相结合,提出了基于神经网络动态逆方法的动力翼伞控制方案,并进行了飞行仿真验证,结果表明完全满足控制要求,具有较好的抗干扰能力和鲁棒性能,对于实现动力翼伞的自主飞行控制具有很好的应用价值。
In view of the difficulty of obtaining accurate math model of power wing umbrella and the complicated coupling of input and output of the system, dynamic model of 8 degrees of freedom wing of power wing was established. The dynamic neural network composed of static neural network and integrator was designed. By using the approximation ability of neural network Combined with the dynamic inverse control method, a dynamic wing control scheme based on the neural network dynamic inverse method is proposed and verified by the flight simulation. The results show that it fully meets the control requirements and has good anti-interference ability and robust performance. The autonomous flight control of the power wing umbrella has good application value.