DocumentCode :
1715025
Title :
The role of a priori knowledge of plant dynamics in neurocontroller design
Author :
Selinsky, J.W. ; Guez, Allon
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
fYear :
1989
Firstpage :
1754
Abstract :
The authors modify an earlier neurocontroller architecture so as to guarantee the performance of the neurocontroller. This architecture uses a priori knowledge of the general structure of the system´s dynamics. The knowledge is utilized for the selection of exploratory schedules to excite selected subsets of the dynamics. The controller does not require a priori knowledge of the exact system dynamics, as they are learned online, nor does it assume the existence of an explicit external teacher. The control architecture developed is not limited to tracking of a prespecified trajectory. The architecture is developed for the control of a robot manipulator
Keywords :
computer architecture; computerised control; learning systems; neural nets; robots; a priori knowledge; exploratory schedules; neurocontroller architecture; neurocontroller design; online learning; plant dynamics; Closed loop systems; Control system synthesis; Control systems; Dynamic scheduling; Manipulator dynamics; Neurocontrollers; Open loop systems; Robot kinematics; Stability; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
Type :
conf
DOI :
10.1109/CDC.1989.70455
Filename :
70455
Link To Document :
بازگشت