基于WNN参数整定的ADRC在火箭炮伺服系统中的应用  

Application of ADRC Based on WNN Parameter Tuning in Rocket Launcher Servo System

作　　者：廖华 侯润民[1] 张志豪 Liao Hua;Hou Runmin;Zhang Zhihao(School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学机械工程学院,南京210094

出　　处：《兵工自动化》2024年第4期14-18,53,共6页Ordnance Industry Automation

摘　　要：针对多管火箭炮交流伺服系统存在变负载、强耦合和不确定性扰动等非线性问题,提出一种优化型小波神经网络自抗扰控制器(WNN-ADRC)。简化电流环节得到被控系统的数学模型,将小波神经网络(waveletneural network,WNN)嵌入自抗扰控制器中进行参数整定,利用分层调整学习速率的方法优化小波神经网络的学习算法得到WNN-ADRC,采用WNN-ADRC控制火箭炮伺服系统,实现对非线性特性的精准估计和补偿。数值仿真结果表明:相对于传统的自抗扰控制器,WNN-ADRC能改善伺服系统的静态响应和动态性能,具有响应速度快、控制精度高的优点。An optimized wavelet neural network active disturbance rejection controller(WNN-ADRC)is proposed to solve the nonlinear problems of multiple rocket launcher AC servo system,such as variable load,strong coupling and uncertain disturbance.The mathematical model of the controlled system is obtained by simplifying the current link,and the wavelet neural network(WNN)is embedded into the ADRC for parameter tuning,and the learning algorithm of the WNN is optimized by using the method of hierarchically adjusting the learning rate to obtain the WNN-ADRC.The WNN-ADRC is used to control the servo system of the rocket launcher to realize the accurate estimation and compensation of the nonlinear characteristics.The numerical simulation results show that the WNN-ADRC can improve the static response and dynamic performance of the servo system,and has the advantages of fast response and high control precision compared with the traditional ADRC.

关 键 词：交流伺服系统 小波神经网络 自抗扰控制器 

分 类 号：TJ391[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]