DocumentCode :
2521814
Title :
Possibility of neural networks controller for robot manipulators
Author :
Yabuta, Tetsuro ; Yamada, Takayuki
Author_Institution :
NTT Transmission Syst. Lab., Ibaraki, Japan
fYear :
1990
fDate :
13-18 May 1990
Firstpage :
1686
Abstract :
NN (neural network) controller characteristics are clarified by comparison with the adaptive control theory. The authors explain the classification of the NN controller architecture and the dynamic NN structure. A comparison between the NN controller and the adaptive controller shows that the framework of a linear two-layer NN controller is the same as that of the adaptive controller, and that the nonlinear three-layer NN (PDP, or parallel distributed processing type) is a nonlinear extension of the adaptive control. The stability characteristics of the NN control system, which shows the robustness effect of the generalized delta rule, the plant and the NN mapping function, are treated. Finally, NN controller experiments are demonstrated using a force control servomechanism. Experimental results suggest that the nonlinear sigmoid function of the NN can compensate for the nonlinear plant effect
Keywords :
force control; neural nets; nonlinear control systems; parallel architectures; robots; stability; adaptive control; controller architecture; force control servomechanism; manipulators; mapping function; neural networks; nonlinear plant effect; nonlinear sigmoid function; robot; stability; three layer networks; two layer networks; Adaptive control; Control systems; Distributed processing; Force control; Manipulator dynamics; Neural networks; Programmable control; Robot control; Robust control; Robust stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 1990. Proceedings., 1990 IEEE International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
0-8186-9061-5
Type :
conf
DOI :
10.1109/ROBOT.1990.126252
Filename :
126252
Link To Document :
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