DocumentCode :
1629598
Title :
Neural networks for process control
Author :
Luebbers, P.G. ; Pandya, A.S.
Author_Institution :
Florida Atlantic Univ., Boca Raton, FL, USA
fYear :
1992
Firstpage :
393
Abstract :
The authors explore many of the current issues involved in adaptive artificial neural network (ANN) controllers. The major issues covered include: exploring basic neural network controller designs described in the literature, new approaches involving the combination of ANN techniques with linguistic based approaches, describing sources of input and output data for parameter estimation, and a framework for comparing adaptive artificial neural network controllers with other adaptive controllers using benchmark examples. In addition, hybrid neural network/fuzzy controllers are described
Keywords :
adaptive control; fuzzy control; neural nets; parameter estimation; process computer control; adaptive artificial neural network; benchmark examples; controller designs; hybrid neural network/fuzzy controllers; linguistic based approaches; parameter estimation; process control; Adaptive control; Artificial neural networks; Computer science; Control systems; Neural networks; Parameter estimation; Process control; Programmable control; Signal processing algorithms; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 1992., IEEE International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-0720-8
Type :
conf
DOI :
10.1109/ICSMC.1992.271743
Filename :
271743
Link To Document :
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