Sliding Mode Force Control of an Electrohydraulic Servo System with RBF Neural Network Compensation

Authors

  • Xinliang LU Shijiazhuang Tiedao University
  • Fengpo DU Southeast University
  • Qian JIA Nanjing Institute of Technology
  • Bin Ren Shijiazhuang Tiedao University
  • Xingsong WANG Southeast University

DOI:

https://doi.org/10.5755/j01.mech.25.1.21279

Keywords:

Electrohydraulic, RBF, Neural network, Sliding mode, Compensation control, Trajectory tracking

Abstract

In this paper, the dynamics of an electrohydraulic servo system is analyzed. It is difficult to achieve the precise force tracking control due to its high nonlinearities and parameter uncertainties. For the accurate force tracking control, a sliding mode control algorithm with radial basis function (RBF) neural network compensation was proposed. The theory verifies that the algorithm is globally asymptotically stable. The experimental results show that the proposed algorithm is not only effective and better than the PID control in the force tracking control, but also robust to external uncertain disturbances.

DOI: http://dx.doi.org/10.5755/j01.mech.25.1.21279

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Published

2019-03-05

Issue

Vol. 25 No. 1 (2019)

Section

DYNAMICS OF MECHANICAL SYSTEMS