DocumentCode :
2191845
Title :
Learning control system for manipulators with the ability to use already acquired knowledge in other problem
Author :
Hayakawa, Soichiro ; Oka, Toshiaki ; Suzuki, Tatsuya ; Okuma, Shigeru
Author_Institution :
Dept. of Electr. Eng., Nagoya Univ., Japan
Volume :
1
fYear :
1996
fDate :
18-21 Mar 1996
Firstpage :
283
Abstract :
The conventional learning control system doesn´t have the capability of generalization, because input data for one trajectory, acquired by learning, cannot be applied to other trajectories. In this paper, we propose the new learning control system with the neural network. The neural network can acquire and memorize the dynamics of the system based on the data obtained from conventional learning process. By using this system, we can obtain the well-approximated input data for any trajectory
Keywords :
learning (artificial intelligence); manipulators; neurocontrollers; learning control system; manipulators; neural network; Control systems; Error correction; Humans; Knowledge engineering; Manipulators; Neural networks; Process control; Robots; Trajectory; Transfer functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Motion Control, 1996. AMC '96-MIE. Proceedings., 1996 4th International Workshop on
Conference_Location :
Mie
Print_ISBN :
0-7803-3219-9
Type :
conf
DOI :
10.1109/AMC.1996.509419
Filename :
509419
Link To Document :
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