DocumentCode :
292018
Title :
Nonlinear adaptive control design using on-line trained neural networks
Author :
Morles, Eliezer Colina
Author_Institution :
Dept. Sistemas de Control, Univ. de Los Andes, Merida, Venezuela
Volume :
2
fYear :
1994
fDate :
2-5 Oct 1994
Firstpage :
1453
Abstract :
An artificial feedforward neural network is used for online control of a certain class of partially known single-input, single-output dynamic systems. The neural network´s task is to provide an approximation of the unknown input-output behavior of the dynamic system to the controller in order to drive the system´s behaviour according to specifications given by a reference model. The error correction-based learning algorithm used to update the weights of the single layer neural network used in the control scheme allows dynamic adjustment of their values to cope with varying signals coming from the dynamic plant
Keywords :
adaptive control; control system synthesis; feedforward neural nets; learning (artificial intelligence); neurocontrollers; nonlinear control systems; nonlinear dynamical systems; SISO dynamic systems; artificial feedforward neural network; error correction-based learning algorithm; nonlinear adaptive control design; online control; online trained neural networks; single-layer neural network; Adaptive control; Artificial neural networks; Control system synthesis; Control systems; Difference equations; Education; Error correction; Feedforward neural networks; Neural networks; Neurons; Nonlinear dynamical systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
Type :
conf
DOI :
10.1109/ICSMC.1994.400050
Filename :
400050
Link To Document :
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