Vibration control of load for rotary crane system using neural network with GA-based training

Kunihiko Nakazono, Kouhei Ohnishi, Hiroshi Kinjo, Tetsuhiko Yamamoto

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

A neuro-controller for vibration control of load in a rotary crane system is proposed involving the rotation about the vertical axis only. As in a nonholonomic system, the vibration control method using a static continuous state feedback cannot stabilize the load swing. It is necessary to design a time-varying feedback controller or a discontinuous feedback controller. We propose a simple three-layered neural network as a controller (NC) with genetic algorithm-based (GA-based) training in order to control load swing suppression for the rotary crane system. The NC is trained by a real-coded GA, which substantially simplifies the design of the controller. It appeared that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach.

Original languageEnglish
Pages (from-to)98-101
Number of pages4
JournalArtificial Life and Robotics
Volume13
Issue number1
DOIs
Publication statusPublished - 2008

Fingerprint

Vibration control
Cranes
Vibration
Genetic algorithms
Neural networks
Controllers
Feedback
State feedback

Keywords

  • Genetic algorithm
  • Neural network
  • Rotary crane
  • Vibration control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Vibration control of load for rotary crane system using neural network with GA-based training. / Nakazono, Kunihiko; Ohnishi, Kouhei; Kinjo, Hiroshi; Yamamoto, Tetsuhiko.

In: Artificial Life and Robotics, Vol. 13, No. 1, 2008, p. 98-101.

Research output: Contribution to journalArticle

Nakazono, Kunihiko ; Ohnishi, Kouhei ; Kinjo, Hiroshi ; Yamamoto, Tetsuhiko. / Vibration control of load for rotary crane system using neural network with GA-based training. In: Artificial Life and Robotics. 2008 ; Vol. 13, No. 1. pp. 98-101.
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