基于SRWNN-FTSM的舰载火箭炮火控系统研究

Research on Shipborne Artillery Fire Control SystemBased on SRWNN-FTSM

针对舰载火箭炮大功率交流伺服系统存在的非线性特性以及不确定扰动,提出了一种自回归小波神经网络快速终端滑模控制器(SRWNN-FTSM)。基于快速终端滑模强鲁棒性特点,用自回归小波神经网络对模型动态自适应逼近,可有效提高响应速度,鲁棒性。利用SRWNN-FTSM控制器,有效克服了负载扰动、参数变化等不确定因素的影响。根据Lyapunov理论证明了闭环系统稳定性。仿真实验表明:所提方案可以有效提高系统的响应速度以及发射的命中精度。

In view of the nonlinear characteristics and uncertain disturbance of the high-power AC servo system of ship-borne artillery,an auto-regressive wavelet neural network fast terminal sliding mode controller(SRWNN-FTSM)is proposed.Based on the strong robustness of fast terminal sliding mode,the dynamic adaptive approach of the model using autoregressive wavelet neural network can effectively improve the response speed and robustness.The use of the SRWNN-FTSM controller effectively overcomes the effects of uncertainties such as load disturbances and parameter changes.The stability of the closed-loop system is proved according to the Lyapunov theory.Simulation experiments show that the proposed scheme can effectively improve the response speed of the system and the accuracy of the launch.