基于WNN-ADRC的高炮交流伺服系统控制  

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

作　　者：李佳恬 高强[1] 巩晋 侯远龙[1] 李俊杰 Li Jiatian;Gao Qiang;Gong Jin;Hou Yuanlong;Li Junjie(School of Mechanical Engineering,Nanjing University of Science&Technology,Nanjing 210094,China;Navigation&Control Technology Institute of China North Industries Group Corporation,Beijing 100089,China)

机构地区：[1]南京理工大学机械工程学院,南京210094 [2]中国兵器工业导航与控制技术研究所,北京100089

出　　处：《兵工自动化》2020年第11期39-43,68,共6页Ordnance Industry Automation

摘　　要：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。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.

关 键 词：小波神经网络 交流伺服控制 自抗扰控制 LM算法 

分 类 号：TJ35[兵器科学与技术—火炮、自动武器与弹药工程] TP273[自动化与计算机技术—检测技术与自动化装置]