Adaptive control using combined online and background learning neural network

Eric Johnson, Seung Min Oh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 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 languageEnglish (US)
Title of host publication2004 43rd IEEE Conference on Decision and Control (CDC)
Pages5433-5438
Number of pages6
DOIs
StatePublished - Dec 1 2004
Event2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas
Duration: Dec 14 2004Dec 17 2004

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume5
ISSN (Print)0191-2216

Other

Other2004 43rd IEEE Conference on Decision and Control (CDC)
CountryBahamas
CityNassau
Period12/14/0412/17/04

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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