航空兵器2024，Vol.31Issue(1)：133-140,8.DOI:10.12132/ISSN.1673-5048.2023.0104
基于分数阶自适应神经网络的电动舵机伺服系统摩擦干扰补偿控制
A Friction Disturbance Compensation Method for Electromechanical Actuator Based on Fractional Order Adaptive Neural Network
摘要
Abstract
Friction torque disturbance affects the tracking performance of electromechanical actuator servo system,bringing position and speed tracking errors,and even may leading to instability of the servo system.Ai-ming at the problem of poor tracking performance of electromechanical actuator servo system under friction torque disturbance,a FOANN friction compensation algorithm is proposed to estimate and compensate the friction torque.Firstly,base on LuGre friction model,a electromechanical actuator model is established,and the un-measured state variable in the LuGre model is estimated by radial basis function neural network.Secondly,a FOANN controller is designed,and the stability of corresponding closed-loop system is proved by Lyapunov sta-bility theory.Finally,through simulation and experimental platform,the dynamic performance of FOANN is compared with those of traditional PD and MRAC.The simulation and experimental results show that,with the proposed FOANN friction torque compensation algorithm,the tracking errors of both position and velocity of electromechanical actuator servo system are greatly reduced.FOANN algorithm can effectively estimate and com-pensate friction torque,reduce the impact of friction disturbance and enhance the dynamic performance of the servo system.关键词
电动舵机/摩擦/LuGre模型/分数阶控制/自适应控制/径向基神经网络Key words
electromechanical actuator/friction/LuGre model/fractional order control/adaptive control/radial basis function neural network分类
军事科技引用本文复制引用
陈渝丰,徐晓璐,张金鹏,张昆峰,岳强,张文静..基于分数阶自适应神经网络的电动舵机伺服系统摩擦干扰补偿控制[J].航空兵器,2024,31(1):133-140,8.基金项目
省部级基金项目(2022YFB4301302) （2022YFB4301302）
航空科学基金项目(2019010M5001) （2019010M5001）
