基于WNN-ADRC 的高炮交流伺服系统控制

为解决高炮交流伺服系统控制中外界扰动及非线性特性的问题，提出一种基于小波神经网络的改进型自 抗扰控制器(WNN-ADRC)。利用LM(levenberg-marquardt)算法优化小波神经网络，采用优化后的小波神经网络对 扩张状态观测器的误差校正增益系数进行在线整定，设计基于小波神经网络的自抗扰控制器，以实现对非线性特性 的准确估计并予以补偿，并通过仿真实验进行验证。仿真结果证明：该控制策略使系统具有较好的稳态性能，抗干 扰能力强。

AC Servo System Control of Antiaircraft Gun Based on WNN-ADRC

To solve the problems of external disturbance and non-linear characteristics in the positioning control of the servo system of antiaircraft gun, an improved active disturbance rejection controller (WNN-ADRC) based on wavelet neural network is proposed. The Levenberg-marquardt algorithm is used to optimize the wavelet neural network. Using wavelet neural network adjust the error correction gain coefficient in the expanded state observer on-line, design an active disturbance rejection controller based on wavelet neural network to achieve accurate estimation and compensation of nonlinear characteristics, and verified by simulation experiments. Simulation results show that this control strategy makes the system has better steady-state performance and strong anti-interference ability.