基于SRWNN-ADRC的交流伺服系统定位控制  

SRWNN-ADRC Based Positioning Control of AC Servo System

作　　者：李佳恬 高强[1] 侯润民[1] 侯远龙[1] 李俊杰 LI Jiatian;GAO Qiang;HOU Runmin;HOU Yuanlong;LI Junjie(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：《电光与控制》2021年第1期98-102,111,共6页Electronics Optics & Control

摘　　要：针对高炮位置交流伺服系统控制存在的外界扰动以及非线性特性等问题,提出了一种自回归小波神经网络改进型单神经元自抗扰控制器(SRWNN-ADRC)。单神经元自适应控制器(SNAC)将非线性误差反馈控制律中的非线性增益作为其权值系数,利用SRWNN作为辨识器,在线辨识被控对象的梯度信息并将其提供给SNAC。通过SNAC的自学习功能实现ADRC中参数的在线调节。仿真结果证明,此控制策略使系统具有较好的稳态性能,抗干扰能力强,且动态品质也得到了优化。To solve the problems of external disturbances and nonlinear characteristics in the positioning control of the AC servo system of antiaircraft guns,an improved single-neuron Active Disturbance Rejection Controller based on Self-Recurrent Wavelet Neural Network(SRWNN-ADRC) is designed.The Single Neuron Adaptive Controller(SNAC) takes the nonlinear gain in the nonlinear error feedback control law as its weight coefficient.SRWNN is taken as an identifier,through which the gradient information of the controlled object is identified online and supplied to SNAC.Through the self-learning function of SNAC,the parameters in ADRC can be adjusted online.Simulation results show that this control strategy enables the system to have better steady-state performance,stronger anti-interference ability,and an optimized dynamic quality.

关 键 词：自回归小波神经网络 交流伺服控制 自抗扰控制 在线整定 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]