HIGH ORDER SLIDING MODE CONTROL WITH ANTI-SWAY BASED COMPENSATION ON ARTIFICIAL NEURAL NETWORK BY PSO ALGORITHM FOR OVERHEAD CRANE

Authors

  • Le Xuan Hai Đại học Bách khoa Hà Nội
  • Nguyen Van Thai
  • Vu Thi Thuy Nga
  • Hoang Thi Tu Uyen
  • Nguyen Thanh Long
  • Thai Huu Nguyen
  • Phan Xuan Minh

DOI:

https://doi.org/10.15625/2525-2518/55/3/8617

Keywords:

High oder sidling mode control, artificial neural network, partical swarm optimization algorithm (PSO), anti-sway for overhead cranes

Abstract

This paper proposes a second order sliding mode controller combined with signal set calibrator for overhead crane tracking desired position and resisting disturbance. High order sliding mode controller ensures that the overhead crane tracks desired trajectory and resists disturbance. Neural network is trained by particle swarm optimization algorithm (PSO) to compensate anti-sway for load. The results on the computer simulation show that high order sliding mode controller with anti-sway compensation for overhead crane tracks desired trajectory and the swing of load that is smaller than high order sliding mode controller without anti-sway compensation.

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Published

2017-06-16

Issue

Section

Electronics - Telecommunication