针对舰载火箭炮交流伺服系统控制速度与精度的问题, 提出了一种RBF神经网络PID-模糊复合控制策略。该复合控制策略根据误差信息调节两种控制方法对被控对象的作用权值, 使两种控制方法无扰动地切换, 实现最终的控制量连续稳定输出。仿真实验结果表明, 该控制策略较好地综合了RBF神经网络PID控制和模糊控制的优势, 控制精度高, 系统响应快、震荡小, 能够更好地满足舰载火箭炮交流伺服系统的性能指标要求。

Aiming at the control speed and accuracy of the AC servo system of the ship-borne rocket launcher, a composite control strategy combining RBF neural network based PID control with fuzzy control is proposed. The composite control strategy adjusts the weights of the two control methods on the controlled object according to the error information, so as to switch the two control methods without disturbance, and realize the continuous and stable output of the final control quantity. The simulation results show that the control strategy combines the advantage of RBF neural network based PID control with that of fuzzy control, and has high control precision, fast system response speed and small oscillation, which can better meet the performance requirements of the AC servo system of the ship-borne rocket launcher.