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Adaptive backstepping-based neural decentralized control for stochastic switched systems

  • Bohai University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper addresses the problem of decentralized adaptive neural output-feedback control for a class of uncertain switched nonlinear stochastic large-scale systems. A new adaptive neuarl output-feedback controller design method is developed under the framework of backstepping recursive design, adaptive control, and dynamic surface control technique. It is proved that the proposed controller can ensure that all signals of the resulting closed-loop system are the semi-globally uniformly ultimately mean square bounded.

Original languageEnglish
Title of host publicationProceedings - 2016 31st Youth Academic Annual Conference of Chinese Association of Automation, YAC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages261-266
Number of pages6
ISBN (Electronic)9781509044238
DOIs
StatePublished - 3 Jan 2017
Event31st Youth Academic Annual Conference of Chinese Association of Automation, YAC 2016 - Wuhan, China
Duration: 11 Nov 201613 Nov 2016

Publication series

NameProceedings - 2016 31st Youth Academic Annual Conference of Chinese Association of Automation, YAC 2016

Conference

Conference31st Youth Academic Annual Conference of Chinese Association of Automation, YAC 2016
Country/TerritoryChina
CityWuhan
Period11/11/1613/11/16

Keywords

  • adaptive control
  • decentralized control
  • neural network
  • switched systems

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