A simple alternative to neural network control scheme for robot manipulators

Author

Hsia, T.C. ; Jung, Seul

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA

Volume

42

Issue

4

fYear

1995

fDate

8/1/1995 12:00:00 AM

Firstpage

414

Lastpage

416

Abstract

Recent research results have shown that neural network techniques are effective in compensating highly nonlinear uncertainties in the robot model where computed torque method is used for robot motion control. One excellent work was reported by Ishiguro et. al. (1992). The purpose of this note is to present a simple alternate solution to the same control problem which does not require the use of a neural network. The solution is based on the disturbance rejection technique developed by Hsia (1989-92). Computer simulations show that the alternate control method works better

Keywords

control system analysis computing; control system synthesis; digital simulation; manipulators; motion control; nonlinear control systems; uncertain systems; computed torque method; computer simulation; control design; disturbance rejection technique; nonlinear uncertainties; robot manipulators; robot motion control; Computer networks; Computer simulation; Manipulators; Motion control; Neural networks; Robot control; Robust control; Signal generators; Torque control; Uncertainty;

fLanguage

English

Journal_Title

Industrial Electronics, IEEE Transactions on

Publisher

ieee

ISSN

0278-0046

Type

jour

DOI

10.1109/41.402483

Filename

402483