Control of dynamic grasping systems using neural network approximation

Author

Guo, Gongliang ; Gruver, William A. ; Jin, Kai

Author_Institution

Coll. of Eng., Kentucky Univ., Lexington, KY, USA

fYear

1991

fDate

13-15 Aug 1991

Firstpage

196

Lastpage

202

Abstract

A control algorithm for dynamic grasping systems using neural network approximation (NNA) is proposed. The kinematic and dynamic equations of the grasping system are derived. Based on these equations, a method for generalized computed torque control is developed. From computations of this control scheme, four elemental operation functions that are realized by elemental NNA functions are induced. All of the control computations in the grasping system are accomplished using neural network approximation. The PD control of a two-jointed finger mechanism is studied as an example of the application of the algorithm. Results using the NNA functions are compared

Keywords

neural nets; robots; PD control; dynamic equations; dynamic grasping systems; generalized computed torque control; kinematic equations; neural network approximation; two-jointed finger mechanism; two-term control; Approximation algorithms; Computer networks; Control systems; Equations; Fingers; Heuristic algorithms; Kinematics; Neural networks; PD control; Torque control;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 1991., Proceedings of the 1991 IEEE International Symposium on

Conference_Location

Arlington, VA

ISSN

2158-9860

Print_ISBN

0-7803-0106-4

Type

conf

DOI

10.1109/ISIC.1991.187357

Filename

187357