Decentralized Adaptive Neural Approximated Inverse Control for a Class of Large-Scale Nonlinear Hysteretic Systems With Time Delays

Xiuyu Zhang, Yue Wang, Xinkai Chen, Chun Yi Su, Zhi Li, Chenliang Wang, Yaxuan Peng

Research output: Contribution to journalArticle

14 Citations (Scopus)


This paper proposes a decentralized neural adaptive dynamic surface approximated inverse control (DNADSAIC) scheme for a class of large-scale time-delay systems with hysteresis nonlinearities as input. The decentralized control problem under the case only the outputs are measurable is solved by utilizing the radial basis function neural networks approximator and the hysteresis approximated inverse compensator. Also, with the help of finite covering lemma, the traditional Krasovskii functionals are dropped when coping with the delays, leading to the removal of the assumptions on the functions with time-delay states and the acquisition of the arbitrarily small L∞ tracking performance of each hysteretic subsystem with time delays. The analysis of stabilities guarantees all the signals of the closed-loop systems are semiglobally uniformly ultimately bounded. Simulation results illustrate the efficiency of the proposed DNADSAIC scheme.

Original languageEnglish
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Publication statusAccepted/In press - 2018 May 4



  • Adaptive control
  • Control systems
  • Decentralized adaptive control
  • Delay effects
  • dynamic surface approximated inverse control
  • Hysteresis
  • hysteresis
  • Inverse problems
  • L∞ performance
  • large-scale system
  • Large-scale systems
  • Nonlinear systems

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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