Model reference adaptive control using neural networks for synchronization of discrete-time chaotic systems

Jaeho Baek, Jongyo Clioi, Heejin Lee, Euntai Kim, Mignon Park

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

Abstract

This paper presents a model reference adaptive control (MRAC) approach based on neural networks (NN) for the synchronization of a discrete-time chaotic systems. The input of reference model system is chosen using the output of master system and the slave system is the discrete-time chaotic system. We design the adaptive controller using NN so that the controlled slave system achieves asymptotic synchronization with the reference system given that master system and slave system with different conditions and/or different type of model. The parameters of controller which can stabilize the error equation are updated via a projection algorithm. Simulation examples are given to demonstrate the validity of our proposed adaptive method.

Original languageEnglish
Title of host publication2008 International Conference on Control, Automation and Systems, ICCAS 2008
Pages1390-1393
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 International Conference on Control, Automation and Systems, ICCAS 2008 - Seoul, Korea, Republic of
Duration: 2008 Oct 142008 Oct 17

Publication series

Name2008 International Conference on Control, Automation and Systems, ICCAS 2008

Other

Other2008 International Conference on Control, Automation and Systems, ICCAS 2008
Country/TerritoryKorea, Republic of
CitySeoul
Period08/10/1408/10/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Model reference adaptive control using neural networks for synchronization of discrete-time chaotic systems'. Together they form a unique fingerprint.

Cite this