TY - GEN
T1 - Neurocontrol
T2 - IEEE International Conference on Systems, Man, and Cybernetics, SMC 1992
AU - Samad, Tariq
PY - 1992/1/1
Y1 - 1992/1/1
N2 - Artificial neural networks - computational models inspired by the brain - provide several distinctive features relevant to control technology. These include: fine-grained massively parallel architectures; robustness to noise, error and damage; learning and adaptation; and nonlinear analog processing. This paper provides a brief overview of neural networks and discusses several ways they can be used for process identification and control: emulating an existing controller, direct and inverse process modeling, direct adaptive control, optimized nonlinear controller development, and process structure and parameter identification.
AB - Artificial neural networks - computational models inspired by the brain - provide several distinctive features relevant to control technology. These include: fine-grained massively parallel architectures; robustness to noise, error and damage; learning and adaptation; and nonlinear analog processing. This paper provides a brief overview of neural networks and discusses several ways they can be used for process identification and control: emulating an existing controller, direct and inverse process modeling, direct adaptive control, optimized nonlinear controller development, and process structure and parameter identification.
UR - http://www.scopus.com/inward/record.url?scp=84960417888&partnerID=8YFLogxK
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U2 - 10.1109/ICSMC.1992.271747
DO - 10.1109/ICSMC.1992.271747
M3 - Conference contribution
AN - SCOPUS:84960417888
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 369
EP - 374
BT - 1992 IEEE International Conference on Systems, Man, and Cybernetics
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 October 1992 through 21 October 1992
ER -