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Advances in Neurofuzzy Algorithms for Real-time Modelling and Control

Advances in Neurofuzzy Algorithms for Real-time Modelling and Control
Advances in Neurofuzzy Algorithms for Real-time Modelling and Control
This paper reviews the architecture, representation capability, training and learning ability of a class of adaptive neurofuzzy systems for real time modelling and control of unknown nonlinear dynamical processes. Issues relating to learning stability, training laws and parametric convergence, network conditioning, gradient noise, the curse of dimensionality associated with associative memory networks, automatic network construction algorithms, and a series of neurofuzzy control design laws, are discussed together with future critical research issues associated with neurofuzzy systems.
1--16
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Brown, M.
52cf4f52-6839-4658-8cc5-ec51da626049
Bossley, K.M.
de1a2979-b9e9-481e-af09-0b4887f0f360
Mills, D.J.
bd207c8b-fbf0-41da-bba4-b54d9a29804d
Feng, M.
6baf8979-9e8e-482e-9686-6e5e7cb2125a
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Brown, M.
52cf4f52-6839-4658-8cc5-ec51da626049
Bossley, K.M.
de1a2979-b9e9-481e-af09-0b4887f0f360
Mills, D.J.
bd207c8b-fbf0-41da-bba4-b54d9a29804d
Feng, M.
6baf8979-9e8e-482e-9686-6e5e7cb2125a

Harris, C.J., Brown, M., Bossley, K.M., Mills, D.J. and Feng, M. (1996) Advances in Neurofuzzy Algorithms for Real-time Modelling and Control. Engineering Applications of Artificial Intelligence, 9 (1), 1--16.

Record type: Article

Abstract

This paper reviews the architecture, representation capability, training and learning ability of a class of adaptive neurofuzzy systems for real time modelling and control of unknown nonlinear dynamical processes. Issues relating to learning stability, training laws and parametric convergence, network conditioning, gradient noise, the curse of dimensionality associated with associative memory networks, automatic network construction algorithms, and a series of neurofuzzy control design laws, are discussed together with future critical research issues associated with neurofuzzy systems.

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More information

Published date: 1996
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250285
URI: http://eprints.soton.ac.uk/id/eprint/250285
PURE UUID: 4a6b0029-4b33-4834-ae9e-8d0194f2984e

Catalogue record

Date deposited: 04 May 1999
Last modified: 07 Jan 2022 21:08

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Contributors

Author: C.J. Harris
Author: M. Brown
Author: K.M. Bossley
Author: D.J. Mills
Author: M. Feng

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