A fuzzy-logic concept for highly fast and accurate position control of industrial robots

Author

Kuntze, H.-B. ; Sajidman, M. ; Jacubasch, A.

Author_Institution

Fraunhofer-Inst. fur Inf.- und Datenverarbeitung, Karlsruhe, Germany

Volume

1

fYear

1995

fDate

21-27 May 1995

Firstpage

1184

Abstract

Different approaches of a learnable fuzzy-logic (FL) concept for highly fast and accurate position control of industrial robots are presented which provide both time-optimality for large position errors as well as well damped response (no overshoot) near the target. For automatic optimization of the control parameters an additional neural-network component is introduced. Based on simulation and experiments the performance and robustness of the presented FL concept are discussed

Keywords

fuzzy control; fuzzy logic; industrial robots; learning systems; neural nets; optimisation; position control; robots; variable structure systems; automatic optimization; industrial robots; large position errors; learnable fuzzy-logic; neural-network component; position control; robustness; time-optimality; Analytical models; Control systems; Industrial control; Nonlinear control systems; Nonlinear dynamical systems; Optimal control; Position control; Robotics and automation; Robustness; Service robots;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 1995. Proceedings., 1995 IEEE International Conference on

Conference_Location

Nagoya

ISSN

1050-4729

Print_ISBN

0-7803-1965-6

Type

conf

DOI

10.1109/ROBOT.1995.525441

Filename

525441