Paper Title:
Research on a Pneumatic Miniature Robotic Control System Based on Improved Single Neural Network PID Control
  Abstract

Pneumatic miniature robotic control system usually adopts PID (Proportion Integration Differentiation) control strategy at present. To cope with the limitations of the basic PID control strategy, an improved single neural network PID control strategy is put forward in this paper. The control strategy is a single neuron adaptive controller with adjusting weighting coefficient, the weighting coefficient is realized according to the Hebb learning rule with supervisory. Both simulation and experimental results indicate that steady state error of the system equal to zero in the step-response curve, this scheme is a feasible control method for the 3-dof pneumatic miniature robotic control system.

  Info
Periodical
Chapter
Chapter 9: Manufacturing Engineering and Simulation
Edited by
Paul P. Lin and Chunliang Zhang
Pages
2157-2161
DOI
10.4028/www.scientific.net/AMM.105-107.2157
Citation
W. Li, X. Y. Dai, "Research on a Pneumatic Miniature Robotic Control System Based on Improved Single Neural Network PID Control", Applied Mechanics and Materials, Vols. 105-107, pp. 2157-2161, 2012
Online since
September 2011
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Price
$32.00
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