Title :
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
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;
Conference_Titel :
Robotics and Automation, 1995. Proceedings., 1995 IEEE International Conference on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-1965-6
DOI :
10.1109/ROBOT.1995.525441
