DocumentCode :
1647439
Title :
Autonomous learning cerebellum model articulation controller
Author :
Shaaban, Khaled M. ; Mohamed, Refaat M.
Author_Institution :
Dept. of Electr. Eng., Assiut Univ., Egypt
Volume :
1
fYear :
2002
fDate :
6/24/1905 12:00:00 AM
Firstpage :
681
Lastpage :
686
Abstract :
Introduces an intelligent controller named autonomous learning cerebellum model articulation controller (ALCMAC). This controller has the ability to learn its control function incrementally and autonomously from direct interaction with the environment. It combines two features, first there is no need for the system mathematical modeling and second it learns its control function autonomously from direct interaction with the environment. To illustrate its capabilities, it is used to control a two-joint robot arm to track a preplanned trajectory
Keywords :
cerebellar model arithmetic computers; intelligent control; learning systems; neurocontrollers; position control; robots; autonomous learning cerebellum model articulation controller; control function; intelligent controller; preplanned trajectory tracking; two-joint robot arm; Adaptive control; Brain modeling; Control systems; Mathematical model; Neural networks; Process control; Robot control; Table lookup; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
ISSN :
1098-7576
Print_ISBN :
0-7803-7278-6
Type :
conf
DOI :
10.1109/IJCNN.2002.1005555
Filename :
1005555
Link To Document :
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