基于RBFSMC 的舰载武器随动系统控制策略

为解决舰载武器在海上射击时精度不高的问题，提出一种基于RBF 神经网络滑模控制策略。根据舰载武 器随动系统的工作原理，建立舰载武器随动系统数学模型，利用滑模在非线性控制中的优越性，采用RBF 神经网络 对系统的摄动参数进行自适应逼近，解决滑模在切换时产生的抖振问题，得出舰载武器随动系统位置控制器的控制 律。仿真结果表明：该控制策略能提高舰载武器随动系统的快速响应能力和动态精度，满足系统要求。

Control Strategy of Ship Borne Weapon Servo System Based on RBFSMC

A sliding mode control strategy based on RBF neural network is proposed to solve the problem of low accuracy of ship borne weapons when firing at sea. According to the working principle of ship borne weapon servo system, the mathematical model of ship borne weapon servo system is established. By using the superiority of sliding mode in non-linear control, the perturbation parameters of the system are approximated adaptively by RBF neural network to solve the chattering problem caused by sliding mode switching, and control law of the ship borne weapon servo system position controller is obtained. The simulation results show that the control strategy can improve the fast response ability and dynamic accuracy of the ship borne weapon servo system, and meet the system requirements.