Towards hybrid soft computing approach to control of complex systems

Recently an approach to the control of complex systems employing a layered overall structure and different but compatible formalisms for subsystem representations on different levels, which is consistent with most of theoretical results in systems and control sciences, has been subject of extensive...

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Bibliographic Details
Published in2002 1st IEEE Symposium "Intelligent Systems" Vol. 1; pp. 47 - 54 vol.1
Main Authors Dimirovski, G.M., Yuanwei Jing
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Control design
Control systems
Fuzzy systems
Modeling
Neural networks
Process control
Space technology
State-space methods
Systems engineering and theory
Uncertainty
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ISBN0780371348
9780780371347
DOI10.1109/IS.2002.1044227

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Summary:Recently an approach to the control of complex systems employing a layered overall structure and different but compatible formalisms for subsystem representations on different levels, which is consistent with most of theoretical results in systems and control sciences, has been subject of extensive research. It provides a unified framework methodology for resolving system modeling identification and control design for complex multi-variable processes. One alternative of this approach is based on employing state space theory of composite similarity systems and the use of fuzzy systems, the other one makes use of neural networks instead, to deal with uncertainties and control adaptation. From the viewpoint of systems engineering, it may well be implemented within the standard computer process control technology.
ISBN:0780371348
9780780371347
DOI:10.1109/IS.2002.1044227