Verification of Multilayer Neural-Net Controller in Manipulator Tracking Control

Abstract:

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In this paper a multilayer neural-net (NN) controller is applied for tracking control of robotic manipulator, which is a nonlinear object having unknown and changeable parameters. Dynamics equations of a rigid manipulator are presented. The NN controller is used for compensating manipulator nonlinearities. The controller is realized in a form of a multilayer NN, which is nonlinear in the weights. The standard delta rule using backpropagation tuning is inadequate, so a term correcting the delta rule as well as a robustifying term is added. The presented control law and tuning algorithm are derived from the Lyapunov’s direct method. Results of the experiment are presented in this paper.

Info:

Periodical:

Solid State Phenomena (Volume 164)

Edited by:

Andrejus H. Marcinkevičius and Algirdas V.Valiulis

Pages:

99-104

DOI:

10.4028/www.scientific.net/SSP.164.99

Citation:

W. Żylski and P. Gierlak, "Verification of Multilayer Neural-Net Controller in Manipulator Tracking Control", Solid State Phenomena, Vol. 164, pp. 99-104, 2010

Online since:

June 2010

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Price:

$35.00

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