Robust stabilization of fuzzy control for nonlinear multiple time-delay interconnected systems via neural-network-based approach

Feng Hsiag Hsiao*, Yew Wen Liang, Sheng Dong Xu, Chia Yen Lin, Zhi Ren Tsai

*Corresponding author for this work

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

Abstract

The stabilization problem is considered in this study for a nonlinear multiple time-delay large-scale (NMTDLS) system. First, the NN model is employed to approximate each subsystem. Then, an LDI state-space representation is established for the dynamics of each NN model. According to the LDI state-space representation, a robustness design of fuzzy control is proposed to overcome the effect of modeling errors between subsystems and NN models. Next, in terms of Lyapunov's direct method, a delay-dependent stability criterion is derived to guarantee the asymptotic stability of NMTDLS systems. Subsequently, a set of fuzzy controllers is synthesized to stabilize the NMTDLS system.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Fuzzy Systems
Pages484-491
Number of pages8
DOIs
StatePublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Fuzzy Systems - Vancouver, BC, Canada
Duration: 16 07 200621 07 2006

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2006 IEEE International Conference on Fuzzy Systems
Country/TerritoryCanada
CityVancouver, BC
Period16/07/0621/07/06

Keywords

  • Delay-dependent stability criterion
  • Large-scale systems
  • Modeling error
  • Neural network

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