【作者】 宋晓东； 姚晓先； 李志伟；

【Author】 Song Xiaodong Yao Xiaoxian Li Zhiwei (1 School of Aerospace of Science and Engineering Beijing Institute of Technology Beijing 100081 P.R.China; 2 School of Mechanical Engineering Yanshan University Qinhuangdao Hebei 066004 P.R.China)

【机构】 北京理工大学宇航科学技术学院； 燕山大学机械工程学院；

【摘要】 智能泵源可以根据导弹飞行状态的不同,调节泵源的输出流量和压力,能够有效提高液压舵机的效率。本文设计了基于RBF神经网络的智能泵源输出流量补偿器,研究了基于RBF神经网络的系统辨识算法和单层神经网络的输出流量预测算法。比较了输出流量补偿器引入前后的控制效果,验证了基于RBF神经网络的弹载液压舵机智能泵源输出流量补偿器的有效性。更多还原

【Abstract】 The intelligent pumping source can greatly improve the work efficiency of hydraulic actuator by adaptively adjusting its output flow and pressure.In this paper,we proposed an output flow compensation approach based on RBF neural network.Comparisons of control result with and without output flow compensation were made,and the compared results show the intelligent pumping source has better robustness when the output flow compensation based on RBF neural network was utilized.更多还原