Aspects of fuzzy control and estimation
Aspects of fuzzy control and estimation
This paper gives an overview of Fuzzy Systems for application to fuzzy modelling, analysis, control and estimation. This first section describes the major concepts together with future research objectives without requiring any a priori knowledge on the part of the reader. Further sections introduce the mathematical notation required to describe fuzzy systems and review existing application and research areas. The subject of performance analysis tools for fuzzy systems is highlighted as a current research area and an example of a simple analysis tool is given. The topic of signal estimation using fuzzy models is also discussed and a target tracking example is included. Comparisons are also drawn between fuzzy systems and single layer associative memory neural networks that offer some transparency for dynamical processes modelled as neural networks.
201--242
Moore, C.G.
79001bdf-4225-447b-bbe8-cf81c1711906
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
1994
Moore, C.G.
79001bdf-4225-447b-bbe8-cf81c1711906
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Moore, C.G. and Harris, C.J.
(1994)
Aspects of fuzzy control and estimation.
Harris, C.J.
(ed.)
Advances in Intelligent Control.
.
Record type:
Conference or Workshop Item
(Other)
Abstract
This paper gives an overview of Fuzzy Systems for application to fuzzy modelling, analysis, control and estimation. This first section describes the major concepts together with future research objectives without requiring any a priori knowledge on the part of the reader. Further sections introduce the mathematical notation required to describe fuzzy systems and review existing application and research areas. The subject of performance analysis tools for fuzzy systems is highlighted as a current research area and an example of a simple analysis tool is given. The topic of signal estimation using fuzzy models is also discussed and a target tracking example is included. Comparisons are also drawn between fuzzy systems and single layer associative memory neural networks that offer some transparency for dynamical processes modelled as neural networks.
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Published date: 1994
Additional Information:
Address: London, UK
Venue - Dates:
Advances in Intelligent Control, 1994-01-01
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 250274
URI: http://eprints.soton.ac.uk/id/eprint/250274
PURE UUID: dd951196-15dc-42d5-98cd-a507a5ce888e
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Date deposited: 04 May 1999
Last modified: 10 Dec 2021 20:07
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Contributors
Author:
C.G. Moore
Author:
C.J. Harris
Editor:
C.J. Harris
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