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The addition of neural networks to the inner feedback path in order to improve on the use of pre-trained feed forward estimators

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The addition of neural networks to the inner feedback path in order to improve on the use of pre-trained feed forward estimators. / Sanders, David; Haynes, B. P; Tewkesbury, Giles; Stott, I. J.

In: Mathematics and Computers in Simulation, Vol. 41, No. 5-6, 08.1996, p. 461-472.

Research output: Contribution to journalArticle

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Author

Sanders, David ; Haynes, B. P ; Tewkesbury, Giles ; Stott, I. J. / The addition of neural networks to the inner feedback path in order to improve on the use of pre-trained feed forward estimators. In: Mathematics and Computers in Simulation. 1996 ; Vol. 41, No. 5-6. pp. 461-472.

Bibtex

@article{493e85cc386249128e98b001ef71b5cb,
title = "The addition of neural networks to the inner feedback path in order to improve on the use of pre-trained feed forward estimators",
abstract = "A learning control architecture which uses a multi-layer feed forward neural network with error back propagation is described. The architecture includes a feed forward estimator which is pre-trained and a feedback controller which continues to learn. The properties of the architectures are investigated through a series of experiments, and the application of the prototype adaptive controllers is described. To examine the performance of this controller, square wave demand signals are applied to the controller and the results are presented.",
keywords = "Mathematics, neural networks , Simulation, Computers",
author = "David Sanders and Haynes, {B. P} and Giles Tewkesbury and Stott, {I. J}",
year = "1996",
month = aug
doi = "10.1016/0378-4754(95)00093-3",
language = "English",
volume = "41",
pages = "461--472",
journal = "Mathematics and Computers in Simulation",
issn = "0378-4754",
publisher = "Elsevier",
number = "5-6",

}

RIS

TY - JOUR

T1 - The addition of neural networks to the inner feedback path in order to improve on the use of pre-trained feed forward estimators

AU - Sanders, David

AU - Haynes, B. P

AU - Tewkesbury, Giles

AU - Stott, I. J

PY - 1996/8

Y1 - 1996/8

N2 - A learning control architecture which uses a multi-layer feed forward neural network with error back propagation is described. The architecture includes a feed forward estimator which is pre-trained and a feedback controller which continues to learn. The properties of the architectures are investigated through a series of experiments, and the application of the prototype adaptive controllers is described. To examine the performance of this controller, square wave demand signals are applied to the controller and the results are presented.

AB - A learning control architecture which uses a multi-layer feed forward neural network with error back propagation is described. The architecture includes a feed forward estimator which is pre-trained and a feedback controller which continues to learn. The properties of the architectures are investigated through a series of experiments, and the application of the prototype adaptive controllers is described. To examine the performance of this controller, square wave demand signals are applied to the controller and the results are presented.

KW - Mathematics

KW - neural networks

KW - Simulation

KW - Computers

U2 - 10.1016/0378-4754(95)00093-3

DO - 10.1016/0378-4754(95)00093-3

M3 - Article

VL - 41

SP - 461

EP - 472

JO - Mathematics and Computers in Simulation

JF - Mathematics and Computers in Simulation

SN - 0378-4754

IS - 5-6

ER -

ID: 1765798