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Self-correcting wavelet neural network control of continuous rotary electro-hydraulic servo motor
Affiliation:Key Laboratory of Advanced Manufacturing and Intelligent Technology,Ministry of Education,Harbin University of Science and Technology,Harbin 150080,P.R.China;Key Laboratory of Advanced Manufacturing and Intelligent Technology,Ministry of Education,Harbin University of Science and Technology,Harbin 150080,P.R.China;Key Laboratory of Advanced Manufacturing and Intelligent Technology,Ministry of Education,Harbin University of Science and Technology,Harbin 150080,P.R.China
Abstract: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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