Finite Time Controller Design of Nonlinear Quantized Systems with Nonstrict Feedback Form

  • Xueyi Zhang
  • Fang WangEmail author
  • Lili Zhang
Regular Papers Intelligent Control and Applications


This article considers a finite-time control problem of nonlinear quantized systems in complex environments. The controlled system is in a non-strict feedback form. By applying a nonlinear decomposition of hysteretic quantizer, the quantization issue is tackled successfully. By employing a structural property of radial basis function (RBF) neural networks (NNs), the conventional backstepping method is extended to non-strict feedback nonlinear quantized systems. Based on the finite time stability criterion, a new adaptive neural control scheme is presented. The constructed neural controller can ensure the transient performance of nonlinear quantized systems.


Adaptive control finite-time control neural network quantized nonlinear systems 


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© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Foreign LanguagesShandong University of Science and TechnologyQingdaoChina
  2. 2.College of Mathematics and Systems ScienceShandong University of Science and TechnologyQingdaoP. R. China
  3. 3.School of Applied MathematicsGuangdong University of TechnologyGuangzhouP. R. China

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