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NNDI decentralized evolved intelligent stabilization of large-scale systems

  • Chen, Z.Y. (Guangdong University of Petrochem Technol, Sch Sci) ;
  • Wang, Ruei-Yuan (Guangdong University of Petrochem Technol, Sch Sci) ;
  • Jiang, Rong (Guangdong University of Petrochem Technol, Sch Sci) ;
  • Chen, Timothy (Division of Engineering and Applied Science, California Institute of Technology)
  • Received : 2021.05.22
  • Accepted : 2022.03.02
  • Published : 2022.07.25

Abstract

This article focuses on stability analysis and fuzzy controller synthesis for large neural network (NN) systems consisting of several interconnected subsystems represented by the NN model. Advanced and fuzzy NN differential inclusion (NNDI) for stability based on the developed algorithm with H infinity can be designed based on the evolved biological design. This representation is constructed using sector linearity for NN models. Sector linearity transforms a non-linear model into a linear model based on proposed operations. New sufficient conditions are realized in the form of LMI (linear matrix inequalities) to ensure the asymptotic stability of the trans-Lyapunov function. This transforms the nonlinear model into a linear model based on multiple rules. At last, a numerical case study with simulations is derived as illustration to prove its feasibility in real nonlinear structures.

Keywords

Acknowledgement

The authors are grateful for the research grants given to RY Wang from the Projects of Talents Recruitment of GDUPT (NO. 2019rc098) in Guangdong Province, Peoples R China No. 2019rc098 by ZY Chen as well as to the anonymous reviewers for constructive suggestions.

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