Self-correcting wavelet neural network control of continuous rotary electro-hydraulic servo motor

王晓晶; Li Chunhui; Peng Yiwen

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Self-correcting wavelet neural network control of continuous rotary electro-hydraulic servo motor

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摘要

In allusion to the problem of friction,leakage,vibration and noise existing in continuous rotary motor electro-hydraulic servo system,highly nonlinearity and uncertainties affecting the system performance,based on the transfer function of electro-hydraulic servo system,a kind of Pol-Ind friction model is proposed.The parameters of Pol-Ind friction model are identified and the accurate mathematical model of friction torque is obtained by experiment.The self-correcting wavelet neural network(WNN)controller is proposed,and Adam optimization algorithm is used to perform gradient optimization on scale factor and displacement factor in wavelet basis function,so as to improve the speed and precision of parameter optimization.Through comparative simulation analysis,it is clearly that the self-correcting WNN controller can effectively improve the frequency response and tracking accuracy of continuous rotary motor electro-hydraulic servo system.

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来源
《高技术通讯：英文版》 |2021年第1期|26-37|共12页
作者
王晓晶; Li Chunhui; Peng Yiwen;
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作者单位

Key Laboratory of Advanced Manufacturing and Intelligent Technology;

Ministry of Education;

Harbin University of Science and Technology;

Harbin 150080;

P.R.China;

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原文格式 PDF
正文语种 chi
中图分类自动化基础理论;
关键词
continuous rotary electro-hydraulic servo motor; Pol-Ind friction model; self correcting wavelet neural network(WNN); Adam optimization algorithm;

Self-correcting wavelet neural network control of continuous rotary electro-hydraulic servo motor

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