Artificial neural network for identification and tracking control of a flexible joint single-link robot

Author

Kim, Hunmo ; Parker, Joey K.

Author_Institution

Dept. of Mech. Eng., Alabama Univ., Tuscaloosa, AL, USA

fYear

1993

fDate

7-9 Mar 1993

Firstpage

233

Lastpage

237

Abstract

An artificial neural network for identification and tracking control of a nonlinear flexible joint robot with model reference adaptive control structure is developed. Neural network identification (NNI) is used to obtain a dynamic model of a flexible joint robot to be controlled. Once NNI has closely matched the dynamic model of a flexible joint robot, neural network control (NNC) of tracking trajectory of a flexible joint robot is designed. Both tasks are completed using the backpropagation neural network. The method is shown to be a more simple, robust and adaptive learning control system than traditional control design for tracking control of a flexible joint single-link robot

Keywords

backpropagation; identification; model reference adaptive control systems; neural nets; nonlinear control systems; robots; robust control; tracking; artificial neural network; backpropagation neural network; dynamic model; model reference adaptive control structure; neural network control; nonlinear flexible joint robot; single-link robot; tracking trajectory; Adaptive control; Adaptive systems; Artificial neural networks; Backpropagation; Control systems; Neural networks; Nonlinear dynamical systems; Robot control; Robust control; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

System Theory, 1993. Proceedings SSST '93., Twenty-Fifth Southeastern Symposium on

Conference_Location

Tuscaloosa, AL

ISSN

0094-2898

Print_ISBN

0-8186-3560-6

Type

conf

DOI

10.1109/SSST.1993.522777

Filename

522777