Adaptive control using combined online and background learning neural network

Eric N. Johnson; Seung Min Oh

doi:10.1109/CDC.2004.1429672

Adaptive control using combined online and background learning neural network

Eric N. Johnson, Seung Min Oh

Aerospace Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

25 Scopus citations

Abstract

A new adaptive neural network (NN) control concept is proposed with proof of stability properties. The NN learns the plant dynamics with online training, and then combines this with background learning from previously recorded data, which can be advantageous to the NN adaptation convergence characteristics. The network adaptation characteristics of the new combined online and background learning adaptive NN is demonstrated through simulations.

Original language	English (US)
Title of host publication	2004 43rd IEEE Conference on Decision and Control (CDC)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5433-5438
Number of pages	6
ISBN (Print)	0780386825
DOIs	https://doi.org/10.1109/CDC.2004.1429672
State	Published - 2004
Event	2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas Duration: Dec 14 2004 → Dec 17 2004

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	5
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Other

Other	2004 43rd IEEE Conference on Decision and Control (CDC)
Country/Territory	Bahamas
City	Nassau
Period	12/14/04 → 12/17/04

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Access to Document

10.1109/CDC.2004.1429672

Cite this

Johnson, E. N., & Oh, S. M. (2004). Adaptive control using combined online and background learning neural network. In 2004 43rd IEEE Conference on Decision and Control (CDC) (pp. 5433-5438). Article FrC11.4 (Proceedings of the IEEE Conference on Decision and Control; Vol. 5). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2004.1429672

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title = "Adaptive control using combined online and background learning neural network",

abstract = "A new adaptive neural network (NN) control concept is proposed with proof of stability properties. The NN learns the plant dynamics with online training, and then combines this with background learning from previously recorded data, which can be advantageous to the NN adaptation convergence characteristics. The network adaptation characteristics of the new combined online and background learning adaptive NN is demonstrated through simulations.",

author = "Johnson, {Eric N.} and Oh, {Seung Min}",

year = "2004",

doi = "10.1109/CDC.2004.1429672",

language = "English (US)",

isbn = "0780386825",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "5433--5438",

booktitle = "2004 43rd IEEE Conference on Decision and Control (CDC)",

address = "United States",

note = "2004 43rd IEEE Conference on Decision and Control (CDC) ; Conference date: 14-12-2004 Through 17-12-2004",

}

Johnson, EN & Oh, SM 2004, Adaptive control using combined online and background learning neural network. in 2004 43rd IEEE Conference on Decision and Control (CDC)., FrC11.4, Proceedings of the IEEE Conference on Decision and Control, vol. 5, Institute of Electrical and Electronics Engineers Inc., pp. 5433-5438, 2004 43rd IEEE Conference on Decision and Control (CDC), Nassau, Bahamas, 12/14/04. https://doi.org/10.1109/CDC.2004.1429672

Adaptive control using combined online and background learning neural network. / Johnson, Eric N.; Oh, Seung Min.
2004 43rd IEEE Conference on Decision and Control (CDC). Institute of Electrical and Electronics Engineers Inc., 2004. p. 5433-5438 FrC11.4 (Proceedings of the IEEE Conference on Decision and Control; Vol. 5).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - A new adaptive neural network (NN) control concept is proposed with proof of stability properties. The NN learns the plant dynamics with online training, and then combines this with background learning from previously recorded data, which can be advantageous to the NN adaptation convergence characteristics. The network adaptation characteristics of the new combined online and background learning adaptive NN is demonstrated through simulations.

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Adaptive control using combined online and background learning neural network

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

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