Journal of South China University of Technology (Natural Science Edition) ›› 2021, Vol. 49 ›› Issue (3): 25-33.doi: 10.12141/j.issn.1000-565X.200296

Special Issue: 2021年机械工程

• Mechanical Engineering • Previous Articles     Next Articles

Intelligent Control Method for Pump-Valve Parallel Electro-Hydraulic Position Servo System

WANG Chengwen1,2,3  GUO Xinping1  ZHANG Zhenyang1  LIU Hua1   

  1. 1. College of Mechanical and Vehicle Engineering,Taiyuan University of Technology,Taiyuan 030024,Shanxi,China; 2. Key Laboratory of Advanced Transducers and Intelligent Control System of the Ministry of Education,Taiyuan University of Technology,Taiyuan 030024,Shanxi,China; 3. The State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University,Hangzhou 310058,Zhejiang,China
  • Received:2020-06-08 Revised:2020-07-20 Online:2021-03-25 Published:2021-03-01
  • Contact: 郭新平(1994-),男,硕士生,主要从事电液伺服控制研究。 E-mail:15561433629@163.com
  • About author:汪成文(1982-),男,博士,副教授,主要从事电液伺服控制研究
  • Supported by:
    Supported by the Key Research and Development Plan of Shanxi Province ( 201903D121069)

Abstract: In light of the valve control system's advantages of fast response and high energy efficiency,a pumpvalve parallel electro-hydraulic position servo system was proposed,and its intelligent control method is studied. Firstly,a single neuron PID controller,which can realize the self-adaptive adjustment of the weight,is designed for the pump-controlled subsystem of the pump-valve parallel system. Secondly,a RBF ( Radial Basis Function) neural network-based sliding mode controller was designed for the valve-controlled subsystem of the pump-valve parallel system. The Lyapunov function was designed to prove the stability of the closed-loop system. Finally,the co-simulation was conducted by using Matlab /Simulink and AMESim. The co-simulation results show that the single neuron PID controller of the pump-controlled subsystem has better speed tracking control performance than the traditional PID controller. The RBF neural network-based sliding mode controller of the valve-controlled subsystem has better position tracking accuracy and stronger anti-interference ability than the traditional PID controller. The proposed intelligent control method can significantly improve the control performance of the pump-valve parallel system.

Key words: pump-valve parallel system, single neuron, RBF neural network, sliding mode control, intelligent control

CLC Number: