Monitoring and Control of Information-Poor Systems An Approach based on Fuzzy Relational Models
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Form:Einzelkauf Download
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Sprache:Englisch
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eBook Format:PDF
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Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
01.02.2012
Verlag
WileySeitenzahl
312 (Printausgabe)
Dateigröße
11532 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9781119945871
The monitoring and control of a system whose behaviour is highly
uncertain is an important and challenging practical problem.
Methods of solution based on fuzzy techniques have generated
considerable interest, but very little of the existing literature
considers explicit ways of taking uncertainties into account. This
book describes an approach to the monitoring and control of
information-poor systems that is based on fuzzy relational models
which generate fuzzy outputs.
The first part of Monitoring and Control of Information-Poor
Systems aims to clarify why design decisions must take account
of the uncertainty associated with optimal choices, and to explain
how a fuzzy relational model can be used to generate a fuzzy
output, which reflects the uncertainties associated with its
predictions. Part two gives a brief introduction to fuzzy
decision-making and shows how it can be used to design a predictive
control scheme that is suitable for controlling information-poor
systems using inaccurate measurements. Part three describes
different ways in which fuzzy relational models can be generated
online and explains the practical issues associated with their
identification and application. The final part of the book provides
examples of the use of the previously described techniques in real
applications.
Key features:
* Describes techniques applicable to a wide range of engineering,
environmental, medical, financial and economic applications
* Uses simple examples to help explain the basic techniques for
dealing with uncertainty
* Describes a novel design approach based on the use of fuzzy
relational models
* Considers practical issues associated with applying the
techniques to real systems
Monitoring and Control of Information-Poor Systems forms
an invaluable resource for a wide range of graduate students, and
is also a comprehensive reference for researchers and practitioners
working on problems involving mathematical modelling and
control.
uncertain is an important and challenging practical problem.
Methods of solution based on fuzzy techniques have generated
considerable interest, but very little of the existing literature
considers explicit ways of taking uncertainties into account. This
book describes an approach to the monitoring and control of
information-poor systems that is based on fuzzy relational models
which generate fuzzy outputs.
The first part of Monitoring and Control of Information-Poor
Systems aims to clarify why design decisions must take account
of the uncertainty associated with optimal choices, and to explain
how a fuzzy relational model can be used to generate a fuzzy
output, which reflects the uncertainties associated with its
predictions. Part two gives a brief introduction to fuzzy
decision-making and shows how it can be used to design a predictive
control scheme that is suitable for controlling information-poor
systems using inaccurate measurements. Part three describes
different ways in which fuzzy relational models can be generated
online and explains the practical issues associated with their
identification and application. The final part of the book provides
examples of the use of the previously described techniques in real
applications.
Key features:
* Describes techniques applicable to a wide range of engineering,
environmental, medical, financial and economic applications
* Uses simple examples to help explain the basic techniques for
dealing with uncertainty
* Describes a novel design approach based on the use of fuzzy
relational models
* Considers practical issues associated with applying the
techniques to real systems
Monitoring and Control of Information-Poor Systems forms
an invaluable resource for a wide range of graduate students, and
is also a comprehensive reference for researchers and practitioners
working on problems involving mathematical modelling and
control.
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