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网络控制系统取代点对点连接的电缆网,提高了导弹武器系统整体性能,但由于信息传输分时复用总线,系统延时很难避免。在对导弹系统延时进行分析的基础上,利用RBF神经网络良好的预测功能,建立弹体运动模型,设计RBF预测控制器,实现对网络延时的实时补偿,保证了系统的稳定性。通过仿真实验,并与传统PID控制器补偿做比较,验证了该方法的可行性和有效性。
The network control system replaces the cable network of the point-to-point connection, which improves the overall performance of the missile weapon system. However, since the information transmission time-division multiplexed bus, the system delay is hard to avoid. Based on the analysis of the missile system delay, the RBF neural network is used to predict the performance of the system. The projectile motion model is established. The RBF predictive controller is designed to compensate the network delay in real time and ensure the stability of the system. Through the simulation experiment and comparison with the traditional PID controller compensation, the feasibility and effectiveness of this method are verified.