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

IEEE Trans Syst Man Cybern B Cybern. 2008 Feb;38(1):244-51. doi: 10.1109/TSMCB.2006.890304.

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.

Publication types

  • Letter
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Feedback
  • Fuzzy Logic*
  • Models, Theoretical*
  • Neural Networks, Computer*
  • Nonlinear Dynamics*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Time Factors