Robustness design of fuzzy control for nonlinear multiple time-delay large-scale systems via neural-network-based approach

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

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

55 Scopus citations

Abstract

The stabilization problem is considered in this correspondence for a nonlinear multiple time-delay large-scale system. First, the neural-network (NN) model is employed to approximate each subsystem. Then, a linear differential inclusion (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 nonlinear multiple time-delay large-scale systems. Finally, based on this criterion and the decentralized control scheme, a set of fuzzy controllers is synthesized to stabilize the nonlinear multiple time-delay large-scale system.

Original languageEnglish
Pages (from-to)244-251
Number of pages8
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume38
Issue number1
DOIs
StatePublished - 02 2008
Externally publishedYes

Keywords

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

Fingerprint

Dive into the research topics of 'Robustness design of fuzzy control for nonlinear multiple time-delay large-scale systems via neural-network-based approach'. Together they form a unique fingerprint.

Cite this