基于 RBF 神经网络的滚仰式导引头控制系统设计

为保证滚仰式捷联导引头的稳定控制，提出了一种基于 RBF 神经网络整定的 PID 控制策略，用于导引头稳定回路校正环节。根据滚仰式捷联导引头的运动学与动力学关系，结合导引头稳定回路校正环节采用的 RBF 神经网络 PID 控制算法，建立了滚仰式捷联导引头稳定与跟踪一体化仿真模型；仿真结果表明：滚仰式捷联导引头稳定回路采用 RBF 神经网络整定的 PID 控制器后，其动态性能优于传统 PID 控制器，建立的仿真模型能够对机动目标实现快速稳定跟踪，在工程应用中可提供有益参考。

Control System Design Based on RBF Neural Network for Roll-Pitch Seeker

To solve the stability control of roll-pitch strap-down seeker,one kind of PID self-tuning algorithm based on RBF neural network was put forward for the stable loop correction link of the seeker. According to the kinematics and dynamics model of the roll-pitch strap-down seeker,the stability and tracking integrated model was established by using RBF neural network PID controller algorithm. Simulation results show the dynamic performance of PID self-tuning algorithm based on RBF neural network is superior to traditional PID controller for the roll-pitch strap-down seeker.The simulation model of the stability and tracking integrated model not only has stable quickly tracking ability for the maneuvering target,but also can provide a useful reference in the engineering application.