Neurocontrol: Concepts and applications

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


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.

Original languageEnglish (US)
Title of host publication1992 IEEE International Conference on Systems, Man, and Cybernetics
Subtitle of host publicationEmergent Innovations in Information Transfer Processing and Decision Making, SMC 1992
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)0780307208, 9780780307209
StatePublished - 1992
EventIEEE International Conference on Systems, Man, and Cybernetics, SMC 1992 - Chicago, United States
Duration: Oct 18 1992Oct 21 1992

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X


OtherIEEE International Conference on Systems, Man, and Cybernetics, SMC 1992
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 1992 IEEE.


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